Information distribution systems and methods, programs realizing these methods, and information media concerning the programs

ABSTRACT

The achievement of broadband information transmission media, makes it possible to perform on-demand information distribution. With this comes a desire for an autonomous information distribution system that meets both diverse client requirements and the need for a high level of immediacy. 
     An objective of the present invention is to provide such information distribution systems. The systems of the present invention comprise a means for managing the number of distributions, a means for generating an advertising list in which the extraction probability of each information material in the case of random extraction is the ratio of the remaining number of distributions of each information material to the overall remaining number of distributions, a means for handicap application which applies a handicap to the remaining number of distributions of each information material included in the advertising list, and a means for random extraction which performs random extraction with respect to the advertising list so as to extract one information material. In these systems of the present invention, extracted information materials are distributed to a distribution demand terminal from the information distribution server via a network, and the contents of the advertising list are updated.

TECHNICAL FIELD

The present invention relates to information distribution systems andmethods for distributing viewing information, such as video contents, toa viewer terminal connected to a network, as well as programs andinformation media for realizing these methods. More particularly, thepresent invention relates to information distribution systems andmethods for distributing advertisement information together with thedistribution of video contents, and programs and information media forrealizing these methods.

BACKGROUND ART

With the achievement of high communication rates, video contentdistribution services via the Internet have been started. Along withsuch diversification of information media, development is progressing inthe area of various broadband information media, and accordingly, thenumber of viewing channels is increasing. At the same time, with anincrease in bidirectional information media, great changes are foreseenin viewer behavior, including on-demand viewing and so on. These trendsare expected to accelerate even faster in the future.

Along with the above, the average viewing rating for each medium isexpected to gradually decline. In television and radio advertising it isalready becoming difficult to achieve the same advertising effect as inthe past by using advertisements inserted between various contents orwith a part of the contents.

Therefore, in allocating a limited advertising budget between variousinformation media, there is a desire on the part of an advertiser toachieve the best possible cost effectiveness through differentiatedadvertisement distributions, such as those that closely match the tastesof individual distribution viewers, instead of the averaged form ofdistribution, as in the past.

In the distribution of advertising, the number of viewers in a targetedgroup of viewers that are reached by the advertiser (reach) and thenumber of times the advertising reaches viewers, are criteria indicatingthe effectiveness of advertising.

In advertising for television broadcasts, time slots for advertising areestablished for each program (program advertising slots). For eachprogram advertising slot, a prediction is made as to the viewer group(age, gender, and the like) and the degree to which the viewing is done.These predictions are made considering broadcast time, program content,and viewing rating. An advertising broadcast plan (program advertisingslot purchasing plan) is developed in order to respond to the desires ofthe advertiser with regard to reach and frequency for each targetedgroup.

When advertising is distributed via the Internet to a viewer terminalalong with video content, or when an advertisement comprising videoinformation in an information screen is distributed, because it ispossible for the same video content or information screen to distributedifferent advertising depending upon the viewer, the concept of anadvertisement time slot is provided for each viewing time (this iscalled a viewing time advertisement slot).

Compared with the program advertising slot in television broadcasting,the viewing time advertisement slot enables not prediction but ratherspecification of viewers. It enables more precisely targetedadvertising. However, since the number of advertisement slots changesdepending upon the overall viewing time of viewers, it is not possibleto pre-establish an advertisement slot.

In the manual allocations of the past, it was too complex to performdetailed allocation of advertisements in diversified information media,and such a detailed allocation has become increasingly more difficult toaccommodate.

To handle this type of situation, in Japanese Patent Application No.2000-48217 (Unexamined Published Japanese Patent Application No. (JP-A)2001-236444), for example, a method for advertising distribution isproposed. This method prepares and quantifies a plurality of attributescommon to advertisements, determines the distribution frequency anddistribution sequence that reflect distribution conditions from thedistribution side and the viewer side, generates an advertisementsequence schedule, performs scheduling and generates a time schedule foradvertisements for which the distribution time band and distributionsequence have been specified, synthesizes the above-noted two schedulesand performs re-scheduling to create a final distribution schedule, anddistributes advertisements from the distribution side to the viewer sidewhile observing the time, in accordance with this distribution schedule.

Japanese Patent Application No. 2000-53305 (International PublicationNo. 01/89216) proposes a technology aimed at achieving a desired totalnumber of reproductions for the advertisement by generating and managinga plan for the upper limit of the number of placements for eachterminal, considering viewer attributes, and also controlling theplacement sequence in accordance with the desires of the advertiser.

DISCLOSURE OF THE INVENTION

In the above-described advertisement distribution methods, the priorityof advertisement placement is determined in accordance with adistribution frequency that is defined by the product of an attributeand a weighting coefficient. Eventually, priority would be applied tothe number of the advertisements required to fill the advertisementslot. However, in actual advertisement distribution, even applyingoverall priority, it is impossible to perform dramatic distribution inaccordance with the desires of the advertiser or the viewer.

That is, in an advertisement without an advertisement slot, there isvery little probability that a large difference will occur in theadvertising effects between the case in which the n-th advertisement andthe (n+1)-th advertisement are distributed in that sequence, and thecase in which these advertisements are distributed in the reversesequence. Given this, it is expected that the effort required to apply acomplete prioritizing will result in commensurate waste.

Additionally, if a distribution schedule is made using the advertisingdistribution method noted in the Examples of the above-described patentapplications, it is expected that advertisements with no timespecification will appear with an averaged frequency. This is because,for example, at the beginning of the planned time period, onlyadvertisements having a high number of demanded distributions will bedistributed, whereas at the end of the planned time period, the numberof remaining distributions for all advertisements without timespecification will be approximately the same. This type of distributionpattern is certainly significantly different from the distributionpattern originally desired by the advertiser.

Furthermore, there is a risk that even advertisements having low weight,such as those with a low number of distributions, may not reach thedemanded number of distributions within the planned time period, therebyresulting in a breach of the advertising contract.

Therefore there is a strong desire for an advertising distributionsystem that enables autonomous determination of a detailed distributionschedule desired by an advertiser, without the need for troublesomehuman intervention.

In particular, in actual advertisement distribution the classificationof attributes desired by an advertiser is not uniform, and differs witheach advertiser and advertisement. Thus it is difficult to establish afixed routine, and it is not easy to determine a priority sequence.Furthermore, in order to perform distribution with uniform attributes,the agency side must buy up a certain amount of advertisement slots dueto the need to avoid interference with other advertisers.

In addition, methods of inserting advertisements include such methods asthe “spot” type advertisement, in which the information medium isspecified, and the “time” type advertisement, in which the content(program) is specified. This makes determining a priority sequence allthe more difficult.

Furthermore, in actual distribution the possibility must also beconsidered of cases where, in response to the desires of an advertiser,there is a day during which advertising is not possible (a disallowedday), or a time band during which advertising is not allowed (adisallowed time band), or cases in which there are weighted andnon-weighted specifications made for advertising days or advertisingtime bands, and cases in which an advertisement cannot fit into anadvertisement slot because the length of the advertisement contentdiffers. In such cases, the number of reproductions for theadvertisement desired by an advertiser must be fulfilled whilesatisfying these restrictions.

In the real world, in which the above-noted complex cases can beenvisioned, methods such as those of the past, which use uniformdistribution priority sequences, are not effective. It is essential toeither perform advertisement distribution at a level that can satisfythe desires of advertisers by being practically useful or, if that isnot possible, to have a huge amount of human support: a far cry from anautonomous system.

In addition, the technology disclosed in Japanese Patent Application No.2000-533055 (International Publication No. 01/89216) can be appreciatedsince it adopts the view of time in selecting advertisements todistribute. However, it merely adjusts the number of reproductions forthe advertisement heading towards the end of a period of time to meetthe required number for each advertisement, while setting and managingthe upper limit to the number of distribution in each individualterminal. Under actual access conditions, it is not only difficult toperform detailed distribution in accordance with the desires ofadvertisers, but it is also uncertain as to even whether the totalnumber of reproductions for the advertisement for each advertisementwill be achieved.

Given the above, the present invention was made in order to solve theabove-described technical problems.

The present invention (1) is an information distribution system thatdistributes each information material from an information distributionserver to an information demand terminal via an information network,where the information distribution system comprises

a means for managing the number of distributions, where the means storesthe planned number of distributions during a period of time for eachinformation material, the actual number of distributions already madefor each information material, and the remaining number of distributionsfor each information material, which is the difference between these twonumbers of distributions,

a means for generating an advertising list, where the means generates anadvertising list for extraction, in which the extraction probability foreach information material in the case of random extraction is the ratioof the remaining number of distributions for each information materialto the accumulated total of the remaining number of distributions foreach information material at that point in time,

a means for handicap application, which, when performing randomextractions, applies a handicap each time to the remaining number ofdistributions of each information material comprised by the advertisinglist, so that the mean extraction probability is maintained over thetime period, while causing deviation in the extraction probabilitydistribution at each random extraction, and

a means for random extraction, where the means performs randomextractions with respect to the advertising list, based on the remainingnumber of distributions of each information material to which a handicaphas been applied, so as to extract one information material,

and wherein an extracted information material is distributed via theinformation network from the information distribution server to thedistribution demand terminal, an addition is made to the actual numberof distributions already made, a subtraction is made from the remainingnumber of distributions based on the results of the distribution, andthe advertising list is updated so that the distribution results arereflected in the extraction probabilities for next time.

Herein, the term “deviation” refers to the condition in which, in theextraction probability distribution for each individual informationmaterial (comprising advertisements), the extraction probability foreach information material for each time region varies from the meanextraction probability with time, to the extent that there is nofluctuation in the mean extraction probability for each informationmaterial over a predetermined period of time; the condition in which themean extraction probability for each category of information materialvaries from the extraction probability distribution for each categoryfor all the information materials; or a combination of these conditions.

The present invention (2) is an information distribution system that, inresponse to demand from each distribution demand terminal, reads outvarious information from a means of storing an information material anddistributes the read-out information material to the distribution demandterminals via a network, where the system comprises,

a means for managing a remaining number of distributions, where themeans stores the planned number of distributions during a period of timefor each information material, the actual number of distributionsalready made for each information material, and the remaining number ofdistributions for each category of each information material, which isthe difference between these two numbers of distributions,

a means for generating an advertising list, where the means generates anadvertising list for extraction of each category, in which theextraction probability for each information material in the case ofrandom extraction is the ratio of the remaining number of distributionsfor each information material to the accumulated total of the remainingnumber of distributions for each information material at that point intime,

a means for category judgment, where the means judges the category towhich the distribution demand terminal belongs at the time adistribution request is received from a distribution demand terminal,

a means for selecting an advertising list, where the means selects theadvertising list corresponding to the judged category,

a means for handicap application, which, when performing randomextractions, applies a handicap each time to the remaining number ofdistributions of each information material comprised in the advertisinglist, so that the mean extraction probability is maintained over thetime period, while causing deviation in the extraction probabilitydistribution at each random extraction,

a means for random extraction, which performs random extraction withrespect to the advertising list based on the remaining number ofdistributions of each information material to which a handicap has beenapplied, so as to extract one information material;

and wherein an extracted information material is distributed via theinformation network from the information distribution server to thedistribution demand terminal that made the request, an addition is madeto the actual number of distributions already made, a subtraction ismade from the remaining number of distributions based on the results ofthe distribution, and the advertising list is updated so that thedistribution results are reflected in the extraction probabilities forthe next time.

The present invention (3) is the information distribution system of (1)or (2), in which the information material comprises an advertisement.

The present invention (4) is an information distribution systemcomprising at least a video content storage means which stores videocontents, an advertisement storage means which stores advertisementmaterials, and a video content distribution server which selectivelyreads requested video contents from the video content storage means, anddistributes, via a network, the video content to a viewer terminal thathas made a request, and the system further comprises,

an advertisement distribution condition database, which stores at least,for each advertisement, information about the desired number ofreproductions for the advertisement during a planned time period andinformation about specifications of increasing or decreasing withrespect to each category and time period,

a viewer database, which stores at least information about a category towhich each viewer belongs, and information about the viewing history foreach viewer,

a means for predicting the number of distribution demands, whichpredicts the number of demanded distributions within the time period foreach category, based on the information on the viewing history of allviewers,

a means for calculating the number of planned distributions, whichcalculates the number of planned distributions of each advertisement foreach category, so as to balance the number of desired advertisements ofeach advertisement for each category and the number of requesteddistributions for each category,

a means for generating a random extraction advertising list, whichgenerates an advertising list for each category, wherein the extractionprobability for each advertisement in the case of random extraction isthe ratio of the planned number of distributions of each advertisementfor each category to the accumulated total for each category of theplanned number of distributions of all the advertisements,

a means for random extraction, which performs random selection andextraction with respect to the advertising list corresponding to acategory to which the distribution demand terminal belongs, so as toselect one advertisement,

a means for generating a distribution list, which generates adistribution list in which the extraction sequence is used as theadvertisement distribution sequence, by repeating the random extractionof advertisements by the means for random extraction until the demandedadvertisement slots are filled, while updating the advertising list sothat the extraction probabilities for the next time reflect the resultsof the extraction,

a means for managing a distribution list, which stores the distributionlist and outputs the list to an advertisement material distributionserver, and

an advertisement material distribution server which, based on thedistribution list, sequentially and selectively reads a correspondingadvertisement material from the advertisement material storage means,and when the video content is distributed via the information network toa distribution demand terminal which has made a request, performs alinked distribution of the advertisement material.

As described in (4), application of a handicap comprises the control ofthe extraction probability distribution for each category for eachadvertisement so as to approach the desired number of reproductions forthe advertisement while maintaining the mean extraction probability foreach advertisement.

The present invention (5) is the information distribution system of (4),wherein the means of generating a distribution list generates adistribution list in which the extraction sequence is used as theadvertisement distribution sequence, by repeating the random extractionof advertisements by the means for random extraction until the demandedadvertisement slots are filled, while updating each number of planneddistributions of the advertising list by reducing the number of planneddistributions so that there is no return to the advertising list for theextracted advertisement.

The present invention (6) is the information distribution system of (4),wherein the means for generating a distribution list generates adistribution list in which the extraction sequence is used as theadvertisement distribution sequence, by repeating the random extractionof advertisements by the means for random extraction until the demandedadvertisement slots are filled, while multiplying the extractionprobability of each advertisement by a corresponding correctioncoefficient and updating the extraction probability of eachadvertisement in the advertising list so that the extraction probabilityfor the next time reflects the extraction results.

Herein, if the correction coefficient is such that the extractionresults are reflected in each of the extraction probabilities for thenext time, it is applicable. For example, when the number of accumulatedplanned number of reproductions for the advertisement is calculated atthe time of each extraction, and the number of actual reproductions forthe advertisement does not reach that number, it is possible to multiplythe extraction probability of such an advertisement by a correctioncoefficient such that increases the extraction probability.

For example, for an advertisement X for which the number of actualreproductions for the advertisement does not reach the accumulatednumber of planned reproductions for the advertisement, in calculatingthe extraction probability for the d-th day, if

${A\left( {X,{d - 1}} \right)} = {\left\lbrack \frac{\begin{matrix}{{Accumulated}\mspace{14mu}{number}\mspace{14mu}{of}\mspace{14mu}{planned}} \\{{{advertisements}\mspace{14mu}{up}\mspace{14mu}{to}\mspace{14mu}{the}\mspace{14mu}\left( {d - 1} \right)} -} \\{{th}\mspace{14mu}{day}\mspace{14mu}{for}\mspace{14mu}{advertisement}\mspace{14mu} X}\end{matrix}}{\begin{matrix}{{Accumulated}\mspace{14mu}{number}\mspace{14mu}{of}\mspace{14mu}{planned}} \\{{{advertisements}\mspace{14mu}{up}\mspace{14mu}{to}\mspace{14mu}{the}\mspace{14mu}\left( {d - 1} \right)} -} \\{{th}\mspace{14mu}{day}\mspace{14mu}{for}\mspace{14mu}{all}\mspace{14mu}{advertisements}}\end{matrix}} \right\rbrack\mspace{14mu}{and}}$${{B\left( {X,{d - 1}} \right)} = \left\lbrack \frac{\begin{matrix}{{Accumulated}\mspace{14mu}{number}\mspace{14mu}{of}\mspace{14mu}{actual}} \\{{{advertisements}\mspace{14mu}{made}\mspace{14mu}{up}\mspace{14mu}{to}\mspace{14mu}{the}\mspace{14mu}\left( {d - 1} \right)} -} \\{{th}\mspace{14mu}{day}\mspace{14mu}{for}\mspace{14mu}{advertisement}\mspace{14mu} X}\end{matrix}}{\begin{matrix}{{Accumulated}\mspace{14mu}{number}\mspace{14mu}{of}\mspace{14mu}{actual}} \\{{{advertisements}\mspace{14mu}{up}\mspace{14mu}{to}\mspace{14mu}{the}\mspace{14mu}\left( {d - 1} \right)} -} \\{{th}\mspace{14mu}{day}\mspace{14mu}{for}\mspace{14mu}{all}\mspace{14mu}{advertisements}}\end{matrix}} \right\rbrack}\mspace{11mu}$it is possible to perform processing whereby the correction coefficientfor the d-th day is taken as beingA(X,d−1)/B(X,d−1).

The present invention (7) is the information distribution system of anyone of (4) to (6), wherein the advertisement distribution conditiondatabase further stores a category classification for eachadvertisement, and the system further comprises

a means for minimum unit category classification which performs adetailed division, into minimum categories, of the categories for allthe advertisements desired to be distributed during the time period, and

assigning the increase or decrease specifications stored in theadvertisement distribution condition database to the correspondingminimum categories, and then storing the specifications again.

The present invention (8) is the information distribution system of anyone of (4) to (7), wherein the means for calculating the number ofplanned distributions, in order to increase or decrease the initiallyallocated number of reproductions for the advertisement for thespecified category for each advertisement in accordance with the targetspecification, performs a uniform flexible adjustment between theinitially allocated number and the number of reproductions for theadvertisement for categories without target specification for theadvertisement; and uses each of the number of reproductions for theadvertisement to which the increase or decrease adjustment has made asthe planned number of distributions for each category, so that theoverall number of reproductions for the advertisement comprised in eachcategory agrees with the number of demanded number of distributions foreach category, while maintaining the ratio of the number ofreproductions for each advertisement for each category to the overallnumber of planned reproductions for advertisements comprised in eachcategory after the flexible adjustment.

The present invention (9) is the information distribution system of anyone of (4) to (7), wherein the means for calculating the number ofplanned distributions, in order to increase or decrease an initiallyallocated number of reproductions for the advertisement for thespecified category for each advertisement in accordance with the targetspecification, performs uniform flexible adjustment between theinitially allocated number and the number of reproductions for theadvertisement for categories without the target specification for theadvertisement; and takes the number of reproductions for theadvertisement of each advertisement wherein the deficiency or excess ofthe number of reproductions for the advertisement for the categorieswithout the target specification caused by the adjustment is adjustedflexibly and uniformly relative to all the advertisements comprised inthe specified categories, so as to maintain the ratio of the number ofreproductions for the advertisement after the adjustment to the overallnumber, as the number of planned distributions for each category.

The present invention (10) is the information distribution system of anyone of (4) to (7), wherein the means for calculating the number ofplanned distributions takes the number of reproductions for theadvertisement of each advertisement, calculated by the following meansof processing (i) to (v), as the number of planned distribution for eachcategory,

(i) a means of processing for taking an amount obtained by dividing theinitially allocated number of reproductions for the advertisement ofeach category by an integer as the unit adjustment amount, andextracting a number of reproductions for the advertisement correspondingto the unit adjustment amount for each category from the initiallyallocated number of reproductions for the advertisement for thecategory, so that the ratio of the number of reproductions for theadvertisement of each advertisement to the unit adjustment amount foreach category is the same as that of the number of reproductions for theadvertisement of each advertisement to the overall initially allocatednumber,

(ii) a means of processing for adjusting the number of reproductions forthe advertisement of an advertisement with a target specification byincreasing or decreasing in accordance with the target specification inthe unit adjustment amount, and performing uniform flexible adjustmentof a deficiency or excess occurring in the number of reproductions forthe advertisement due to the adjustment relative to the number ofreproductions for the advertisement of each advertisement in categorieswithout the target specification,

(iii) a means of processing for dividing the number of reproductions forthe advertisement for each advertisement in each category after theflexible adjustment into a portion that fits within the unit adjustmentamount and a portion that spills over it, while maintaining the ratio ofthe number of reproductions for the advertisement for each advertisementof each category after the flexible adjustment relative to the overallnumber,

(iv) a means of processing for repeating an integer number of times theprocessing of (ii) to (iii) with respect to the accumulation of thenumber of reproductions for the advertisement for each advertisementspilling over from the unit adjustment amount and the number ofreproductions for the advertisement of each advertisement comprised inthe next unit adjustment,

-   -   (v) a means of processing for taking the number of reproductions        for the advertisement of each advertisement obtained by        accumulating the portion that fits within the unit adjustment        amount for each category as the number of reproductions for the        advertisement in the category on each flexible adjustment.

The present invention (11) is the information distribution systemaccording to any one of (4) to (7), wherein the means for calculatingthe number of planned distributions sets the target function Z, whichcomprises the difference between the desired number of reproductions forthe advertisement adjusted by increasing or decreasing for each categoryfor each advertisement and the number of reproductions for theadvertisement, and uses a mathematical programming method to solve for acombination of the number of reproductions for the advertisement foreach category of each advertisement, so that the value of the targetfunction Z is minimized, and then the solved number of reproductions forthe advertisement for each category of each advertisement is taken asthe number of planned advertisements for each category.

The term “increase or decrease” used herein comprises several meaning.

The present invention (12) is the information distribution system of anyone of (8) to (11), wherein the increase or decrease in accordance withthe specification is an increase or decrease adjustment of the number ofreproductions for the advertisement, so that when the ratio of thenumber of the advertisements before the increase or decrease adjustmentrelative to the overall number of reproductions for the advertisement inthe category is compared with that after the increase or decreaseadjustment relative to the overall, the specified ratio of increase ordecrease is achieved.

The present invention (13) is the information distribution system of anyone of (8) to (11), wherein the increase or decrease in accordance withthe specification further performs the increase and decrease adjustmentof (12) after an increase or decrease adjustment of the number ofreproductions for the advertisement so as to achieve the ratio ofincrease or decrease specified after the adjustment.

The present invention (14) is an information distribution systemcomprising at least a video content storage means which stores videocontents, an advertisement storage means which stores advertisementmaterials, and a video content distribution server which selectivelyreads a requested video content from the video content storage means,and distributes the video content to a viewer terminal that has made therequest via a network; and the system further comprises

an advertisement distribution condition database, which stores, for eachadvertisement, at least information about the desired number ofreproductions for the advertisement during a planned time period, andinformation about a specification of increasing or decreasing withrespect to each category,

a viewer database, which stores at least information about a category towhich each viewer belongs, and information about the viewing history foreach viewer,

a means for predicting the number of distribution demands, which, basedon the information about the viewing histories of all viewers, predictsthe number of demanded distributions within the time period for eachcategory,

a means of generating an as yet unallocated advertising list, whichgenerates an as yet unallocated advertising list for each advertisementcomprising the number of remaining advertisements of the overall numberof desired advertisements during the planned time period for eachadvertisement,

a means of generating an initial allocation advertising list, whichmultiplies the as yet unallocated advertising list for eachadvertisement by the ratio of the number of demanded distributions foreach of the categories to the total number, so as to generate an initialallocation advertising list allocated to each category,

a means for calculating a post-increase/decrease adjusted number ofdesired advertisements, which determines for each category for eachadvertisement the initially allocated number of desired advertisementsand the number of desired advertisements after the increase or decreaseadjustment,

a means for calculating the number of planned distributions, whichcalculates the number of planned distributions of each advertisement foreach category by calculating a category weight for each category foreach advertisement, so as to balance between the post-increase/decreaseadjusted number of desired advertisements and the number of demandeddistributions for each category, and multiplying the number of demandeddistributions for each category and the calculated category weight,

a means for generating a pre-allocated advertising list, which generatesan advertising list for each category, in which the extractionprobability for each advertisement in the case of a random extraction isthe ratio of the number of planned distributions of each advertisementfor each category to the overall accumulation of the number of planneddistributions for each category,

a means for calculating handicap, which, with respect to thepre-allocated advertising list for each category, calculates a handicapthat varies the number of planned distributions of each advertisementcomprised in the pre-allocated advertising list, so as to causedeviations in the extraction probability distribution for eachadvertisement during each time region while maintaining the meanextraction probability of each advertisement over the period of time,

a means for generating a next time region advertising list, which usesthe handicap to extract an advertising list for each category for thenext time region from the pre-allocated advertising list for eachcategory,

a means for category judgment, which, when a distribution request isreceived from a distribution demand terminal, judges the category towhich said terminal belongs,

a means for selecting an advertising list, which selects the next timeregion advertising list corresponding to the judged category,

a means for random extraction, which performs random extraction withrespect to the selected next time region advertising list so as toextract one advertisement,

a means for generating a distribution list, which generates adistribution list by using the means for random extraction to repeatrandom extractions until the advertisement slots that have been demandedare filled, while updating the next time region advertising list so thatthe results of the extraction are reflected in each extractionprobability for the next extraction, and which uses the extractionsequence as the advertisement distribution sequence,

a means for managing a distribution list, which stores the distributionlist and outputs it to an advertisement material distribution server,and

an advertisement material distribution server which, based on thedistribution list, sequentially and selectively reads a correspondingadvertisement material from the advertisement material storage means,and which, when the video content is distributed via an informationnetwork to the distribution demand terminal which has made the request,performs linked distribution of the advertisement material.

With regard to processing by the various means in (14), the means forpredicting the number of distribution demands, the means for generatingan as yet unallocated advertising list, the means for generating aninitial allocation advertising list, the means for calculating apost-increase/decrease adjusted number of desired advertisements, themeans for calculating the number of planned distributions, and the meansfor generating a pre-allocated advertising list can be performedmonthly, and wherein

the means for calculating handicap can calculate a handicap for a timeregion in units of days and that for a time region in units of timebands, and

the means for generating the next time region distribution list canconsecutively generate the distribution lists for the next day and forthe next time band, or

the means for predicting a number of distribution demands and the meansfor generating the as yet unallocated advertising list can be performedmonthly,

the means for generating an initial allocation advertising list, themeans for calculating a post-increase/decrease adjusted desired numberof reproductions for the advertisement, the number of planneddistributions calculation method, and the means for generating apre-allocated advertising list can be performed daily,

the means for calculating handicap can calculate a handicap for a timeregion in units of days and that for a time region in units of timebands, and

the means for generating the next time region distribution list canconsecutively generate the distribution lists for the next day and forthe next time band, and also

each of the processing in the above means can be performed when adistribution request is received from a distribution demand terminal.

That is, in the present invention (14), the calculation processing forthe number of distribution demands for each category by the means forcalculating the number of planned distributions of (4) uses onlycategory weighting, and also a function which causes deviation in theextraction probability distributions of each advertisement for each timeregion is added by specifying a disallowed time band in which theadvertisement is not permitted and a target time band in which, comparedwith another time band, there is more concentrated advertising.

The present inventions (15) to (23) are the systems of (14), whereinwith the technical features in (5) to (13) are further specified.

The present invention (15) is the information distribution system of(14), wherein the means for generating a distribution list generates adistribution list in which the extraction sequence is used as theadvertisement distribution sequence by repeating the random extractionof advertisements by the means for random extraction until the demandedadvertisement slots are filled, while updating each number of planneddistribution of the advertising list so that subtraction is made fromthe number of planned distributions for the extracted advertisement andthere is no return to the selected next time region advertising list.

The present invention (16) is the information distribution system of(14), wherein the means for generating a distribution list generates adistribution list in which the extraction sequence is used as theadvertisement distribution sequence, by repeating the random extractionof advertisements by the means for random extraction until the demandedadvertisement slots are filled, while multiplying the extractionprobability of each advertisement by a corresponding correctioncoefficient and updating the extraction probability of eachadvertisement in the selected next time region advertising list so as toreflect the results of the extraction in the next extractionprobability.

Herein, in performing extractions of each advertisement, subtraction isbasically made from the number of planned distributions, and the numberof planned distributions is updated as the remaining number ofdistributions, the updated value being used to determine the number ofadvertisements in the advertising list at the time of extraction as theproduct of the number of planned distributions of each advertisementwith its handicap, and the advertising probability is determined fromthe number of advertisements. However, when a correction coefficient isdetermined as in (16), it is not absolutely necessary to use the actualnumber of remaining planned distributions in this determination.

That is, as shown in the following equation, by multiplying theinitially planned number of distributions during the planned time periodby the handicap that reflects the results of the extractions until thistime, it is possible to calculate a value corresponding to the number ofremaining planned distributions for each advertisement in theadvertising list.Number of advertisements f at the time of extraction in the advertisinglist=Handicap×Initial planned number of distributions during the plannedtime period.

Furthermore, in the embodiment of (16), there is no need to perform theupdating of the remaining number of distributions at the same time ascalculating the handicap. It is possible to update the remaining numberof distributions over a shorter span than the period for calculating thehandicap (the planned time period).

Stated differently, while the calculation of the handicap is performedto adjust the deviation when disallowed distributions and targetspecifications are expected to be comprised at the start of the timeperiod, the updating of the remaining number of distributions isperformed within a relatively short span, so that adjustment is madebefore fluctuations occurring in actual operation accumulate or expand.

The available planned time period comprises three types: monthly, daily,and real time. The combinations of handicap calculation and updating ofthe remaining number of planned distributions can be as shown in thefollowing table. (However, “monthly”; “daily”; or such are merelyexamples of a planned time period, and there is no restriction thereto.It is possible to set a desired time period.)

Updating the number of planned Handicap calculation distributions Realtime Daily Monthly Real time Possible Possible Possible Daily — PossiblePossible Monthly — — Possible

Furthermore, in actual operation, when the timing is such that updatingthe remaining number of planned distributions and handicap calculationare simultaneous, calculation of the extraction probability need notmultiply the handicap and the remaining number of planned distributions,but will result in the same value as using only the handicapcalculation.

An embodiment in which updating of the remaining number of planneddistributions can be achieved in timing different to that of handicapcalculation is the present invention (17).

The present invention (17) is the information distribution system of(16), wherein the means for generating a next time region advertisinglist can update the number of planned distributions of eachadvertisement in the advertising list without changing the handicapcalculated by the means for calculating handicap.

The present invention (18) is the information distribution system of anyone of (14) to (17), wherein

the advertisement distribution condition database further stores acategory classification for each advertisement, the system furthercomprising

a means for minimum unit category classification, which finely dividesthe category classification of all of the advertisements desired to bedistributed during the time period into classifiable minimum categories,and wherein

the increase or decrease specifications stored in the advertisementdistribution condition database are assigned to the correspondingminimum unit categories and stored again.

The present invention (19) is the information distribution system of anyone of (14) to (18), wherein

the means for calculating the number of planned distributions uniformlyand flexibly adjusts the initially allocated number of reproductions forthe advertisement with the target specification for the specifiedcategory using category weight, so as to increase or decrease inaccordance with the target specification, relative to the number ofreproductions for the advertisement for categories without targetspecification for the advertisement, and while maintaining the ratio ofthe number of reproductions for the advertisement for each category ofeach advertisement after the flexible adjustment to the planned numberof reproductions for the advertisement for each advertisement, thecategory weight for the advertisement is calculated by dividing each ofthe number of reproductions for the advertisement which has beenadjusted by increasing or decreasing so that the total number ofreproductions for the advertisement in each category corresponds to thenumber of distribution demands for each category, by the remainingnumber of distribution demands for the category.

The present invention (20) is the information distribution system of anyone of inventions (14) to (18), wherein the means for calculating thenumber of planned distributions adjusts uniformly and flexibly theinitially allocated number of each advertisement with a targetspecification for the specified category so as to increase or decreasein accordance with the target specification, relative to the number ofthe advertisements for categories without target specification for eachadvertisement, and

when a deficiency or excess of the number of reproductions for theadvertisement for the categories without target specification derivedfrom the flexible adjustment is uniformly and flexibly adjusted relativeto all of the advertisements comprised in the categories with the targetspecification so as to maintain the ratio of the adjusted number ofreproductions for the advertisement to the overall number for thecategories, the category weight for each advertisement can be calculatedby dividing the number of reproductions for the advertisement of eachadvertisement by the remaining number of distribution demands for thecategory.

The present invention (21) is the information distribution system of anyone of (14) to (18), wherein the means for calculating the number ofplanned distributions takes the value obtained by dividing the number ofreproductions for the advertisement for each advertisement calculated bythe following means of processing (i) to (v), by the number ofdistribution demands for the category as the category weight for thatcategory of the advertisement,

-   -   (i) a means of processing for pulling out the number of        reproductions for the advertisement corresponding to a unit        adjustment amount for each category from the initially allocated        number of reproductions for the advertisement for each category,        wherein the unit adjustment amount is defined as the initially        allocated number of reproductions for the advertisement for each        category that has been divided by an integer, so that the ratio        of the number of reproductions for the advertisement for each        advertisement to the unit adjustment amount for each category        becomes the same as that of the number of reproductions for the        advertisement for each advertisement to the total initially        allocated number of reproductions for the advertisement for each        category,

(ii) a means of processing for adjusting the number of reproductions forthe advertisement of an advertisement with a target specification byincreasing or decreasing in accordance with the target specification,and performing uniform flexible adjustment of a deficiency or excessoccurring in the number of reproductions for the advertisement by theincrease or decrease adjustment relative to the number of reproductionsfor the advertisement of each advertisement in categories without targetspecification,

(iii) a means of processing for dividing the number of reproductions forthe advertisement for each advertisement in each category after theflexible adjustment into a portion fitting within the unit adjustmentamount and that spilling over the unit adjustment amount, whilemaintaining the ratio of the number of reproductions for theadvertisement of each advertisement for each category after the flexibleadjustment relative to the overall number,

(iv) a means of processing for repeating (ii) to (iii) an integer numberof times with respect to the accumulation of the number of reproductionsfor the advertisement for each advertisement spilling over from the unitadjustment amount and the number of reproductions for the advertisementfor each advertisement comprised in the next unit adjustment,

(v) a means of processing for taking the number of reproductions for theadvertisement for each advertisement obtained by accumulating theportion that fits within the unit adjustment amount for each category oneach flexible adjustment as the number of reproductions for theadvertisement in the category.

The present invention (22) is the information distribution system of anyone of (14) to (18), wherein the means for calculating the number ofplanned distributions sets the target function Z, which comprises thedifference between the number of desired reproductions for theadvertisement adjusted by increasing or decreasing and the number ofactual reproductions for the advertisement for each category of eachadvertisement, and uses a mathematical programming method for solvingthe combination of the number of reproductions for the advertisement foreach category of each advertisement so that the value of the targetfunction Z is minimized, and wherein the category weight of the categoryfor the advertisement is calculated by dividing the solved number ofreproductions for the advertisement for each category for eachadvertisement by the number of distribution demands for the category.

The present invention (23) is the information distribution system of anyone of (19) to (22), wherein increasing or decreasing in accordance withthe specification means adjusting by increasing or decreasing the numberof reproductions for the advertisement so that, when the ratio of thenumber of reproductions for the advertisement for the advertisementbefore the increase or decrease adjustment relative to the overallnumber of reproductions for the advertisement in the category iscompared with that of the number of reproductions for the advertisementfor the advertisement after the increase or decrease adjustment relativeto the overall, the specified ratio of increase or decrease is achieved.

The present invention (24) is the information distribution system of anyone of (14) to (22), wherein the increase or decrease adjustment inaccordance with the adjustment specification means performing theincrease or decrease adjustment of (23) after adjusting the number ofreproductions for the advertisement by increasing or decreasing it so asto achieve the specified ratio of increase or decrease.

As described above, the present inventions of (14) to (24) correspond to(5) to (13), the only difference being in the inventions to which theyare dependent.

In the present inventions (25) to (31) below, a means for calculatinghandicap for causing deviation for each time region in (14) (to (24)) isspecified.

The present invention (25) is the information distribution system of anyone of (14) to (24), wherein the means for calculating handicapcomprises a means for calculating a disallowed date coefficient, a meansfor calculating a target date coefficient, a means for calculating adisallowed time band calculation, and a means for calculating a targettime band coefficient, the product of the coefficients calculated bythese calculation means being taken as the handicap coefficient, and thevalue of the product is the ratio of the number of planned distributionsfor the next time region, which is determined so as to maintain theaverage advertising probability during the time period, relative to thenumber of remaining distributions at the end of the current time region.

The present invention (26) is the information distribution system of(25), wherein

the number of reproductions for the advertisement for an advertisementfor which a disallowance is specified during a specified time region isuniformly distributed over a time region for which there is nodisallowance specification, an increase or decrease adjustment is donewith respect to the number of reproductions for the advertisement foradvertisements without disallowance specification so as to coincide witheach of the total number of planned advertisements in the specifieddisallowed time region and a time region without the disallowancespecification, and then the disallowance coefficient is obtained bydividing the resulting number of reproductions for the advertisement foreach advertisement by the number of remaining distributions of theadvertisement in the time region, and

the number of reproductions for the advertisement for an advertisementfor which there is a target specification in the time region of thetarget specification is uniformly procured from the number ofreproductions for the advertisement for the advertisement for whichthere is a target specification without the target specified time regionso as to increase in accordance with the target specification, whilemaintaining the ratio of the number of reproductions for theadvertisement for each advertisement to the overall number in each timeregion after procurement, the overall number of reproductions for theadvertisement in the time region is adjusted by increasing or decreasingso as to coincide with the planned number of reproductions for theadvertisement in that time region, and then the target coefficient iscalculated by dividing the resulting number of reproductions for theadvertisement for each advertisement in each time region by theremaining number of distributions of the advertisement in the plannedtime period.

The present invention (27) is the information distribution system of(25), wherein

the number of reproductions for the advertisement of an advertisementfor which a disallowance is specified during a disallowancespecification time region is uniformly allocated over a time region forwhich there is no disallowance specification, uniform extraction isperformed from the number of reproductions for the advertisement of anadvertisement for which there is no disallowance specification, whilemaintaining the ratio of the number of reproductions for theadvertisement of an advertisement not with a disallowance specificationin a time region without the disallowance specification time region soas to be the same as the allocated amount, the extracted number ofreproductions for the advertisement is used to compensate the deficiencyin the disallowance specification time region, and the disallowancecoefficient is obtained by dividing the resulting number ofreproductions for the advertisement of each advertisement by theremaining number of distributions of each advertisement in that timeregion, and

in order to increase the number of reproductions for the advertisementof an advertisement for which there is a target specification in thetime region of the target specification, uniform procurement isperformed from the number of reproductions for the advertisement of theadvertisement for which there is a target specification without thetarget specification time region, while maintaining the ratio of thenumber of reproductions for the advertisement of each advertisement inthe time region of the target specification to the overall number ofreproductions for the advertisement after the procurement, thedeficiency in the number of reproductions for the advertisement in atime region without the target specification caused by the procurementis compensated by the number of all advertisements comprised in thetarget specification time region to which the number of reproductionsfor the advertisement corresponding to the procured amount has beentarget specified, and the target coefficient is obtained by dividing theresulting number of distributions of each advertisement by the remainingnumber of distributions of the advertisement during the planned timeperiod.

The present invention (28) is the information distribution system of(25), which uses the values obtained by dividing the number ofreproductions for the advertisement of each advertisement, calculated bythe following means of processing (i) to (v), by the number of remainingdistributions of the advertisement in the planned time period,

(i) a means of processing for taking an amount obtained by dividing theremaining number of reproductions for the advertisement in thedistribution slot of each time region by an integer as the unitadjustment amount, and extracting a number of reproductions for theadvertisement corresponding to the unit adjustment amount for each timeregion from the remaining number of reproductions for the advertisementfor that time region so that the ratio of the number of reproductionsfor the advertisement for each advertisement to the unit adjustmentamount is the same as that of the number of reproductions for theadvertisement of each advertisement to the overall remaining number ofreproductions for the advertisement in each time region,

(ii) a means of processing for performing flexible adjustment thatincreases or decreases the number of reproductions for the advertisementof an advertisement with an adjustment specification within the unitadjustment amount in accordance with the adjustment specification, andfor uniformly allocating the number of reproductions for theadvertisement adjusted by decreasing among time regions other than theadjustment specification, or uniformly procuring the number ofreproductions for the advertisement adjusted by increasing from thenumber of reproductions for the advertisement of advertisements havingan adjustment specification in the time region other than the adjustmentspecification time region,

(iii) a means of processing for dividing the number of reproductions forthe advertisement for each advertisement for each time region after theflexible adjustment into a portion that fits within the unit adjustmentamount, and a portion that spills over it, while maintaining the ratioof the number of reproductions for the advertisement of eachadvertisement in the time region after the flexible adjustment relativeto the overall number,

(iv) a means of processing for repeating (ii) to (iii) an integer numberof times with respect to the accumulation of the number of reproductionsfor the advertisement for each advertisement spilling over from the unitadjustment amount, and that for each advertisement comprised in the nextunit adjustment,

(v) a means of processing for taking the number of reproductions for theadvertisement of each advertisement obtained by accumulating for eachtime region the portion fitting within the unit adjustment amount as thenumber of reproductions for the advertisement in that time region.

The present invention (29) is the information distribution system of(25), wherein the various coefficients are taken as the values obtainedby setting a target function Z, which comprises the difference betweenthe number of reproductions for the advertisement and the desired numberof reproductions for the advertisement adjusted by increasing ordecreasing in accordance with the adjustment specification for eachcategory of each advertisement, using a mathematical programming methodfor solving for a combination of the number of reproductions for theadvertisement for each category of each advertisement so that thefunction Z is minimized, and dividing the resulting number ofreproductions for the advertisement for each category of eachadvertisement by the number of remaining distributions of theadvertisement within the planned time period.

The present invention (30) is the information distribution system of anyone of (26) to (29), wherein the increase or decrease adjustment inaccordance with the adjustment specification is an increase or decreaseadjustment of the number of reproductions for the advertisement, so thatwhen the ratio of the number of reproductions for the advertisement ofthe advertisement before the adjustment relative to the overall numberin the time region is compared with that after the adjustment relativeto the overall number, the specified ratio of increase or decrease isachieved.

The present invention (31) is the information distribution system of anyone of (26) to (29), wherein the increase or decrease adjustment inaccordance with the adjustment specification is the increase or decreaseadjustment of (30) after performing an increase or decrease adjustmentof the number of reproductions for the advertisement so as to achievethe specified ratio of increase or decrease.

The present invention (32) is the information distribution system of anyone of (14) to (31), wherein each time when the means for generating adistribution list performs a random extraction, if an advertisementwhich has been extracted at a previous time or reaches the upper limitof the number of distributions, the result of the extraction that timeis made invalid, and a random extraction is performed again.

In actual distribution, there is a specified slot for an advertisement,and it is necessary to select an advertisement material that willgenerally fit into the slot. One of the approaches for doing this in thepresent inventions (34) to (37) is to perform an operation thatmultiplies the extraction probability by a correction coefficient, whichis a coefficient of slot size in seconds.

The method for calculating the coefficient of slot size in seconds isnot particularly limited thereto.

The present invention (33) is the information distribution system of anyone of (14) to (32), wherein

the advertisement slot condition database further stores the slot sizein seconds for each advertisement material and the slot pattern of eachvideo content, and furthermore stores a coefficient of slot size inseconds for each advertisement, which has been multiplied so that anextraction probability that is not dependent on the size of the slotsize in seconds can be obtained from a decision tree of the combinationpatterns of slot patterns and the number of seconds of eachadvertisement material, and the means for generating a distribution listhas an additional extraction probability adjustment function ƒ or theslot size in seconds, which when performing a random extraction,selectively reads from the advertisement slot condition database theslot size in seconds in accordance with the combination of slot patternand advertisement material so that the extraction probability for eachadvertisement material is the product of the original extractionprobability and the coefficient of slot size in seconds.

The present invention (34) is the information distribution system of anyone of (14) to (32), wherein the advertisement slot condition databasefurther stores the slot size in seconds for each advertisement and theslot pattern for each video content, which system comprises a means forcalculating an expected value, where that means, from a decision tree ofthe combination of patterns of the slot pattern and the number ofseconds for each advertisement material, calculates an expectedextraction value for each advertisement material at each firstextraction of each advertisement slot, and a weight calculation means,which, based on the respective expected values, calculates weightsproportional to the number of planned distributions for eachadvertisement material, and wherein upon the first extraction of anadvertisement slot, the original extraction probabilities for eachadvertisement material is multiplied by the weights to add an extractionprobability adjustment function ƒ or the slot size in seconds.

The present invention (35) is the information distribution system of anyone of (14) to (32), wherein the advertisement slot condition databasefurther stores the slot size in seconds for each advertisement materialand the slot pattern for each video content, which system comprises anmeans for calculating an expected value, which calculates the expectedvalue of the number of advertisement seconds with regard to alladvertisement material within the advertising list, and a means forcalculating the frequency of extractions, which calculates the number ofextraction times for the expected value of slot size in seconds based onthe slot size in seconds and the expected value of the number ofadvertisement seconds for each advertisement, and wherein with respectto each advertisement slot, random extraction is performed atfrequencies calculated by the means for calculating the frequency ofextractions.

The present invention (36) is the information distribution system of anyone of (14) to (32), wherein the advertisement slot condition databasefurther stores the slot size in seconds for each advertisement materialand the slot patterns for each video content,

which system comprises a means for calculating an expected value, wherethat means calculates the expected value of the number of advertisementseconds with regard to all advertisement material within the advertisinglist, a means for calculating the frequency of extractions, which, basedon the value of slot size in seconds and the expected value of slot sizein seconds for each advertisement, calculates the frequency ofextractions so that the value of slot size in seconds for eachadvertisement coincides with the expected value of slot size in seconds,a means for generating a decision tree, which generates a decision treeof the number of extractions and arranges branches that do not satisfyan allowed slot limit based on the combination pattern of the slotpattern and the number of advertisement material seconds, and a meansfor calculating the coefficient of slot size in seconds, whichcalculates the coefficient of slot size in seconds based on the arrangeddecision tree,

and wherein an extraction probability adjustment function for the slotsize in seconds is added, in which the extraction probability of eachadvertisement material is the product of the original extractionprobability and the coefficient of slot size in seconds.

In addition, the present invention (37) enables change of the manner inwhich the attributes are separated in the attribute judgments of (1) to(36).

The present invention (37) is the information distribution system of anyone of (1) to (36), wherein

the advertisement slot conditions database further stores informationabout a specified medium class for each advertisement, the specificationof video content class, and the advertisement slot class,

the means for category judgment also judges considering the informationmedia class of the viewer terminal which made a viewing request, thevideo content class of the viewing request, and the advertisement slotclass, and an advertising list for the classes has been providedbeforehand when performing a category judgment, and

the advertising list selection means selects a class-dedicatedadvertising list for that class when a judgment is made that the aboveclass is selected.

The present inventions (38) to (74) are information distribution methodscorresponding respectively to (1) to (37). The present invention (75) isa program for causing a computer to execute the steps according to anyone of the information distribution methods of (38) to (74). The presentinventions (76) and (77) are respectively an information-recordingmedium which can make the program of (75) computer-readable to executethe program, and an information-transmitting medium which can transmitthe program within an information network.

BRIEF DESCRIPTIONS OF THE DRAWINGS

FIG. 1 is a drawing showing the overall configuration of anadvertisement information distribution system that is an embodiment ofthe present invention.

FIG. 2 is a drawing showing the overall flow of processing of thepresent invention.

FIG. 3 is a drawing describing the present invention's minimum unitcategory setting.

FIG. 4 is a drawing describing the present invention's process ofdetermining the actual allocated number of each advertisement for eachcategory.

FIG. 5 is a drawing showing the present invention's flow from receipt ofan advertisement order to daily processing

FIG. 6 is a drawing showing the present invention's flow from theuploading of a pre-allocated advertising list to the generation of analready-checked advertising list

FIG. 7 is a drawing showing the present invention's flow of calculatingvarious handicap coefficients.

FIG. 8 is a drawing describing the present invention's day unitallocation and the definition of handicap coefficients.

FIG. 9 is a drawing describing the advertisement allocation method(method I) of the present invention.

FIG. 10 is a drawing showing the flow of calculating the disallowed datecoefficient when using method I allocation of the present invention.

FIG. 11 is a drawing showing the flow of calculating target datecoefficient when using method I allocation of the present invention.

FIG. 12 is a drawing showing the flow of calculating the disallowed timeband coefficient when using method I allocation of the presentinvention.

FIG. 13 is a drawing showing the flow of calculating target time bandcoefficient when using method I allocation of the present invention.

FIG. 14 is a drawing describing the advertisement allocation method(method II) of the present invention.

FIG. 15 is a drawing showing the flow of calculating the disallowed datecoefficient when using method II allocation of the present invention.

FIG. 16 is a drawing showing the flow of calculating target datecoefficient when using method II allocation of the present invention.

FIG. 17 is a drawing showing the flow of calculating the disallowed timeband coefficient when using method II allocation of the presentinvention.

FIG. 18 is a drawing showing the flow of calculating target time bandcoefficient when using method II allocation of the present invention.

FIG. 19 is a drawing describing the advertisement allocation method(method III) of the present invention.

FIG. 20 is a drawing showing the flow of calculating the disallowed datecoefficient when using method III allocation of the present invention.

FIG. 21 is a drawing showing the flow of calculating target datecoefficient when using method III allocation of the present invention.

FIG. 22 is a drawing showing the flow of calculating the disallowed timeband coefficient when using method III allocation of the presentinvention.

FIG. 23 is a drawing showing the flow of calculating target time bandcoefficient when using method III allocation of the present invention.

FIG. 24 is a drawing describing the calculation of the amount ofincrease in the advertisement allocation method of the present invention(part 1).

FIG. 25 is a drawing describing the calculation of the amount ofincrease in the advertisement allocation method of the present invention(part 2).

FIG. 26 is a drawing describing the calculation of the amount ofincrease in the advertisement allocation method of the present invention(part 3).

FIG. 27 is a drawing showing the flow of calculating the target categoryweight when using the advertisement allocation method (method I) of thepresent invention.

FIG. 28 is a drawing showing the flow of calculating the target categoryweight when using the advertisement allocation method (method II) of thepresent invention.

FIG. 29 is a drawing showing the flow of calculating the target categoryweight when using the advertisement allocation method (method III) ofthe present invention.

FIG. 30 is a drawing illustrating the present invention's calculationmethod (1) for calculating the coefficient of advertisement slot size inseconds.

FIG. 31 is a drawing illustrating the present invention's calculationmethod (2) for calculating the coefficient of advertisement slot size inseconds.

FIG. 32 is a drawing illustrating the present invention's calculationmethod (4) for calculating the coefficient of advertisement slot size inseconds.

FIG. 33 is a drawing showing the present invention's flow from receiptof a viewer request to distribution list removal.

FIG. 34 is a drawing showing an example of a pre-allocated advertisinglist of the present invention.

FIG. 35 is a drawing showing an example of a pre-checked advertisinglist of the present invention.

EXPLANATION OF NUMERALS

-   -   1. Advertisement material distribution server    -   2. Viewer terminal    -   3. Program video server    -   4. Advertisement server    -   5. Pre-allocated advertising list    -   6. Advertisement distribution conditions database    -   7. Advertising insertion system    -   8. Pre-allocated advertising list uploading process    -   9. Allowance checked advertising list generation and updating    -   10. Handicap coefficient calculation    -   11. Request acceptance    -   12. Various checking processes    -   13. Distribution list generation process    -   14. Used rule checking process    -   15. Database    -   16. Allowance management server

BEST MODE FOR CARRYING OUT THE INVENTION

FIG. 1 shows an embodiment of the overall configuration of the presentinvention, which is a system comprising an advertisement insertionsystem and an associated peripheral system.

The viewer terminal 2 is a terminal that can be connected to a network,and that comprises software for playing back video content provided viathe network.

The program video server 3 stores video content to be distributed to theviewer terminal 2, and specifically comprises a program video contentdatabase and distributes various program video content via the network.

The advertisement material distribution server 1 comprises anadvertisement content database that stores advertisement content createdby an advertiser, and distributes the advertisement content to eachviewer terminal via the network. The number of advertisement servers 1,and program video content servers 3, can be one or more.

The program video content that is distributed by the program videoserver 3 comprises a program that sends a request for advertisementinformation via the network to acquire and play back advertisementcontent from the advertising server 1, during the playback of videocontent. This request is sent together with viewer information held inthe viewer terminal 2.

Additionally, the allowance management server 16 comprises an allowanceinformation database that stores various allowance information such asexpiring date, and sends allowance information regarding storedadvertisement content to the advertisement insertion system 7.

The advertising server 4 comprises a distribution conditions database 6that stores advertisement distribution information, such as the numberof reproductions for the advertisement of advertisement content anddistribution time periods. The pre-allocated advertising list generationprocessor 5 performs allocation that satisfies the distributionconditions.

(Overall Flow)

The general flow of processing of the present invention up until thedetermination of an advertisement to be distributed is described. Asshown in FIG. 2, the flow of the present invention is generally dividedinto the monthly processing process in advertising server 4, the dailyto hourly processing process by advertisement insertion system 7, andthe on-line process that comprises random extraction.

Processing begins by predicting viewer actions for each viewer categorybased on a past viewer log and receiving an order from an advertiserregarding the number of reproductions for the advertisement for eachviewer category. Based on this information, a monthly plan is generatedfor the optimum allocation of an advertisement. By doing this, anadvertising list that is optimally allocated for each category(hereinafter called a “pre-allocated advertising list”) is generated.Furthermore, the planned period is not limited to a monthly period.

Together with the generation of a pre-allocated advertising list, aviewer viewing prediction is made based on time classes such as datesand times, weekdays, and holidays. This is used as information forcalculating the handicap coefficient, described later.

Processing in the advertisement insertion system 7 begins withprocessing 8, which is the uploading of a pre-allocated advertisinglist, as a result of the monthly processing by the advertising server 4.Following this, daily or time-band processing and on-line processing areperformed. In the daily processing, after deleting advertisements thathave already been distributed from the pre-allocated advertising list,an advertising list for the current day is generated. An advertisinglist for each time band is generated in the same manner as by hourlyprocessing.

When there is a request from the viewer terminal 2 for a distribution, apre-allocated advertising list for the time period and corresponding tothe terminal category is used to perform random extraction. Adistribution list is then generated which lists the advertisementsselected by the random extraction in the extraction sequence. The randomextraction is repeated until the requested advertisement slots arefilled.

(Minimum Unit Category)

In the present invention, the advertisement slots are not set in unitsof programs, but rather in numbers of viewings by a target viewer group.Specifically, viewers are classified into categories, based on criteriasuch as age, gender, family makeup, region of residence, hobbies,tastes, past actions and behavior. The advertiser, in placing an order,specifies the level of emphasis in the frequency of distributions toeach of the desired categories. Furthermore, the present inventionencompasses an embodiment where a unique category for each advertisementcan be set up.

FIG. 3 shows a general view of the emphasis in this free-categorysetting type of advertisement allocation method. The example shown inFIG. 3 is one in which each of the individual advertisers performscategory division based on the criterion of viewer age. Both advertisersA and B set age categories, although the age steps are unique to eachadvertiser.

In the present invention, a minimum unit category is determined whichenables the category boundaries of both advertisers to be reflected, andthe values of emphasis setting are assigned with respect to theseminimum unit categories. Although this case describes division into agecategories, it will be understood that obtainable viewer informationitems, such as gender and family makeup, can also be used as criteriafor division into categories.

Using the free setting method of categories, it is possible with thesame system to accommodate various types of category settings, evenwithout buying up advertisement slots in units of information media.Therefore, it is possible to distribute advertising to meet the desiresof the advertisers.

(Determining the Actual Number of Allocations)

With respect to each category, it is then necessary to determine theextent to which viewing should be caused during a predetermined plannedtime period (for example, in units of months). Specifically, the numberof times opportunities to view each advertisement are to be allocated toeach category are determined. FIGS. 4 and 5 show an example of theconfiguration of the apparatus and the processing flow for the method ofdetermining the viewing opportunities allocated to each category(hereinafter called the “actual number of allocations”).

First, the predicted number of viewing slots during the planned timeperiod is statistically calculated from data with regard to the viewinghistory (log) such as the distribution list generation log 15-7, thenumber of viewings predicted for all the advertisements in units ofcategories are summed up, and the predicted number of slots for eachcategory is determined (top drawing, FIG. 4). This is the number ofdemanded distributions for each category during the planned time period.

Then, based on the above, the number of reproductions for theadvertisement for each base category of the individual advertisements(before adjustment) is determined. Specifically, by multiplying by theratio of the number of predicted number of slots for each categoryrelative to the overall number of predicted slots, the initiallyallocated number of desired advertisements for each category and eachadvertisement is obtained (second graph from the top, FIG. 4).

Additionally, with respect to the above, emphasis processing isperformed as specified by the advertiser. Specifically, the number ofreproductions for the advertisement in the categories emphasized asdescribed above is adjusted by increasing or decreasing, so as to takeinto consideration the desires of the advertiser (third graph in FIG.4). The product of the increase/decrease specification accessed from theadvertisement conditions database 6 and the above-noted initiallyallocated desired number of reproductions for the advertisement is takento be the desired number of reproductions for the advertisement for eachcategory after adjustment by increasing or decreasing.

The desired number of reproductions for the advertisement afteradjustment by increasing or decreasing completely reflects the desiresof the advertiser.

The increase or decrease specifications herein are slightly restricted.For example, when all categories are adjusted for emphasis, adjustmentmight not be possible within the desired number of reproductions for theadvertisement. Thus, there is an intrinsic limitation with regard to thenumber of categories, and the degree of increase or decrease, that canbe specified.

The overall total desired number of reproductions for the advertisementafter increase or decrease adjustment is not balanced at this stage withrespect to the number of demanded distributions.

Given the above, for example, a target function Z is taken as total ofthe absolute value, which is the difference between the desired numberof reproductions for the advertisement after increase or decreaseadjustment and the number of actual reproductions for the advertisement.Z is then divided by the desired number of reproductions for theadvertisement after the increase or decrease adjustment. An number ofactual reproductions for the advertisement for each advertisement typeduring the planned time period is determined for each category so as tominimize this target function Z. This is the pre-allocated monthlyadvertising list that serves as the population of the basic randomextraction for each category. An example of this list is shown in FIG.34.

The above-described processing is performed in the pre-allocatedadvertising list generation processor 5 shown in FIG. 1 (5 in FIG. 5).The number of reproductions for the advertisement accessed from thedistribution conditions database 6 is allocated in order to approach thedesired number of reproductions for the advertisement after increase ordecrease adjustment for each of the categories, so that the number ofdistribution demands for each category is not exceeded, whileconsidering the increase or decrease specification.

Category weights are used as coefficients for obtaining the number ofreproductions for the advertisement corresponding to the result of thisallocation from the number of distribution demands for each category.

The category weights are calculated by the following process.

Category Weight Calculation

CM_SIZE: Number of advertisements

CATEGORIES: Number of categories

a(i, j): Increase/decrease specification

#i=1, 2, 3, . . . , CM_SIZE j=1, 2, 3, . . . , CATEGORIES

-   1. Initially allocated number of reproductions for the advertisement    (n0(i,j)) calculation

${n\; 0\left( {i,j} \right)} = {{N(i)} \times {log\_ ctgy}{(k)/{\sum\limits_{k}\mspace{14mu}{{log\_ ctgy}(k)}}}}$k = 1, 2, …  , CATEGORIES

log_ctgy (k): Number of distribution demands for each category

N(i): Desired number of reproductions for the advertisement

-   2. Determining the desired number of allocations (n1(i,j))

With i=0, 1, 2, 3, . . . , CM_SIZE, and j=1, 2, 3, . . . , CATEGORY,

-   i) If advertisement i targets category j,    n1(i,j)=n0(i,j)+u(i,j), and-   ii) For other targets (that is, on day j of the advertisement i    targets category j),

${n\; 1\left( {i,d} \right)} = {{n\; 0\left( {i,j} \right)} - {n\; 0\left( {i,j} \right)*{\sum\limits_{k \in {T\; 1}}{{u\left( {i,k} \right)}/{\sum\limits_{k \in {T\; 2}}{n\; 0\left( {i,k} \right)}}}}}}$

T1: category set of advertisement i

T2: category set without the target specification of advertisement i

where,

${u\left( {i,d} \right)} = \frac{{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)*{\sum\limits_{m}{n\; 0\left( {m,j} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,j} \right)}} - {n\; 0\left( {i,j} \right)} - {{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)}}$m = 1, 2, …  , CM_SIZE.

-   3. Search for the ideal number of allocations (n2(i, j))

An n2(i,j) combination is determined by using mathematical programmingso that the target function X value shown below is minimum.

Target Function:

$Z = {{\sum\limits_{i,j}\left\{ {{K\left( {i,j} \right)} \times {\frac{{n\; 1\left( {i,j} \right)} - {n\; 2\left( {i,j} \right)}}{n\; 1\left( {i,j} \right)}}} \right\}}->\min}$i = 1, 2, …  , CM_SIZE  j = 1, 2, 3, …  , CATEGORIES${K\left( {i,j} \right)} = \left\{ \begin{matrix}1 & {\left( {{{if}\mspace{14mu}{a\left( {i,j} \right)}} = 0} \right)//{{No}\mspace{14mu}{target}\mspace{14mu}{specification}}} \\k & {({otherwise})//{{Target}\mspace{14mu}{specification}}}\end{matrix} \right.$

-   -   with arbitrary integer k        Restriction Conditions:

${\sum\limits_{j}{n\; 2\left( {i,j} \right)}} = {\sum\limits_{j}{n\; 0\left( {i,j} \right)}}$${\sum\limits_{i}{n\; 2\left( {i,j} \right)}} = {\sum\limits_{i}{n\; 0\left( {i,j} \right)}}$

-   -   i=1, 2, 3, . . . , CM_SIZE.//Total number of reproductions for        the advertisement for advertisement i    -   j=1, 2, 3, . . . , CATEGORY//Category j slot

-   4. Calculation of weight function (E)    E(i,j)=n′(i,j)/N(i)

Although in the above-described example, mathematical programming isused to determine the category weight, various other calculation flowscan be used. The specific flows and equations are shown in FIGS. 27 to29. These calculation flows will be described in detail as part of thecalculation method for the handicap coefficients to be presented later,from which it is easy to infer the significance of the flows andequations in FIGS. 27 to 29.

An “1) Increasing/decreasing adjustment” and “2) Expansion/compressionadjustment”; noted in “(1) Calculation of the ideal number ofallocations (n′(i,j)” in the category weight calculation flow of FIG.27, are carried out by the following process.

-   1. Increasing/decreasing adjustment-   <1> For i=1, 2, 3, . . . , CM_SIZE and j=1, 2, 3, . . . ,    CATEGORIES, the number of allocations n1(i,d) is determined in    accordance with the following conditions i) and ii).-   i) when advertisement i specifies category j as a target:    n1(i,j)=n0(i,j)+u(i,j)-   ii) when advertisement i does not specify category j as a target:

${n\; 1\left( {i,j} \right)} = {{n\; 0\left( {i,j} \right)} - {n\; 0\left( {i,j} \right)*{\sum\limits_{k \in {T\; 1}}{{u\left( {i,k} \right)}/{\sum\limits_{k \in {T\; 2}}{n\; 0\left( {i,k} \right)}}}}}}$

T1: category set of advertisement i target specification

T2: category set without the target specification

where,

${u\left( {i,j} \right)} = \frac{{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)*{\sum\limits_{m}{n\; 0\left( {m,j} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,j} \right)}} - {n\; 0\left( {i,j} \right)} - {{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)}}$m = 1, 2, …  , CM_SIZE.

-   2. Expansion/compression adjustment-   <1> For j=1, 2, 3, . . . , CATEGORIES, the expansion/compression    ratio (es) for arranging advertisement slots while maintaining the    ratio for each advertisement is determined.

${{{es}(j)} = {{\sum\limits_{i}{{n\left( {i,j} \right)}/{\sum\limits_{i}{n\; 1\left( {i,j} \right)\mspace{14mu}{for}\mspace{14mu} i}}}} = 1}},2,3,\ldots\mspace{11mu},{CM\_ SIZE}$

-   <2> At each of i=1, 2, 3, . . . , CM_SIZE, for j=1, 2, 3, . . . ,    CATEGORIES, the expansion/compression ratio for each day is used to    determine the ideal number of allocations.    n(i,j)=n1(i,j)*es(j)    (Daily Processing)

Considering the system load when executing processes and processingefficiency, the present invention also encompasses an embodiment inwhich an additional advertising list is generated daily for that day.

Specifically, as shown in FIGS. 5 and 6, the pre-allocated monthlyadvertising list is uploaded (8), processing such as checking theadvertisement's original and allowed time period is checked, and thenthe number of remaining advertisements is checked. Further, theuploading process 9 is carried out, such as checking the number ofremaining times in order to remove advertisements that have already beenadvertised, thereby narrowing the already-allocated advertising list.The results obtained from this processing are stored in thepre-allocated advertising list database 15-2.

(Handicap Coefficient Calculation)

Based on the pre-allocated advertising list generated in this manner,allocation processing to each day and to each time band is performed inthe planned time period. In this allocation task, it is actuallypossible to obtain results that appear to be the same as when themonthly advertising list is allocated to the advertising list for eachday or each time band within the planned time period, by the calculationprocess 9 of multiplying a coefficient by the number of remainingadvertisements for each advertisement in the pre-allocated monthlyadvertising list.

Therefore, because in reality there are fluctuation factors such asdisallowed days, target dates, disallowed time bands, and target timebands, as shown in FIG. 7, coefficients for each of the factors arecalculated and then the products of these coefficients and the number ofremaining advertisements at each point in time are used to obtain apre-checked advertising list serving as the number of reproductions forthe advertisement for an advertisement at the point in time.

The basic idea of the method for calculating the coefficients that serveas handicaps for the above-noted fluctuation factors is described below:

First, handicaps for each category at each point in time, for each dayand each time band and the like, can be set into the advertisementdistribution conditions within the sales unit for allocation.

Herein, the term “sales unit” refers to one division unit which has beendivided arbitrarily based on program information, and “category” refersto one division unit which has been further divided by viewerinformation or the like in the sales unit. Simply put, one pre-allocatedmonthly advertising list is generated from one sales unit.

The term “handicap” is a setting that is provided for increasing ordecreasing the viewing frequency of target specified advertisementcontent under the restriction conditions imposed by the desired numberof reproductions for the advertisement for each advertisement. This termmeans the amount of increase or decrease in the number of distributionswhen exchange is made to the number of distributions, which correspondsto “deviation” in the extraction probability distribution. That is, byadjusting the handicap setting, it is possible to arbitrarily increaseor decrease the distribution probability of an advertisement in acertain day or time band or the like, during the planned time period.

The specific methods for calculating the handicap at each point in timeare described in detail below.

In overall flow, calculations are performed in the sequence ofdisallowed day coefficient calculation, target date coefficientcalculation, disallowed time band coefficient calculation, and targettime band coefficient calculation, as indicated above (FIG. 7). Theproduct of all the coefficients can be used to calculate the overallhandicap coefficient. The results are stored in the pre-checkedadvertising list database, and are used as basic data when performingrandom extractions.

Before describing the specific methods for calculating each of theindividual coefficients, the method for allocating the monthlyadvertising list to each time period and the handicap in this methodwill be described below, using FIG. 8.

Since it is possible to grasp the number of remaining advertisements ofeach type of advertisement at a given time, and approximately predictthe number of reproductions for the advertisement expected on that dayfrom the past viewing history and the like (overall number ofreproductions for the advertisement varies between days), the predictednumber of reproductions for the advertisement can be taken as the idealnumber of allocations on that day.

As described earlier, the advertising list used as a base is determinedfrom the ratios relative to the overall number. Thus, when it is notdesired to perform some special processing for all advertisements onthat day, because it is sufficient simply to compress by the ratiobetween the remaining number of distributions and the ideal number ofallocations, the handicap coefficient is that ratio.

Next, in a case in which an advertisement A is prohibited from beingplaced on the day n+2, as shown in FIG. 8 (hereinafter, referred to as adisallowed day), the number of reproductions for the advertisement foradvertisement A is zero, and this portion should be filled in withadvertisements B and C. Additionally, in order to comply with the numberof reproductions for the advertisement desired by the advertiser for theadvertisement A during the period of time, the advertisement ofadvertisement A that could not be done on day n+2 must be shifted toother days, so as to increase the number of reproductions for theadvertisement of advertisement A on these days. On the other hand,because there is an excessive distribution of advertisements B and C onday n+2, the advertisement thereof must be reduced accordingly on otherdays.

In addition to a disallowance specification, there is the case in whichthe advertiser desires to place emphasis on distribution on a specificday. In FIG. 8, when there is a desire to emphasize distribution ofadvertisement B on day n+1 (hereinafter called a “target day”), theallocations are not in proportion to the number of remainingdistributions for each advertisement, as in the case of disallowancespecification.

Methods for calculating the ideal number of allocations, that is, thevarious handicap coefficients, are described in further detail below.Several methods for calculating handicap coefficients can be used.

(Method I)

The simplest method will be described first. As shown in FIG. 9, when adisallowed day is set, treatment between the disallowed day and otherdays differs. If an advertisement with a disallowed day setting isremoved so as not to be distributed on a disallowed day, an openingoccurs in the advertisement slot on the disallowed day. On the otherhand, because the removed portion is uniformly allocated to days otherthan the disallowed day, the predicted number of advertisement slots onthose days is surpassed (this process corresponds to operation “1” inFIG. 9).

Given the above, while maintaining the ratios for each advertisementtype, increasing or decreasing adjustments (referred to asexpansion/compression adjustment in the Figures) of the amount ofadvertisements are carried out so that the size of the advertisementslot is adjusted to that predicted (this process corresponding tooperation “2” in FIG. 9). By doing this, even if there is a disallowedday, it is possible to approximately maintain the advertisementprobability throughout the planned time period.

Even if there is a target day specification, the distribution of theadvertisement of interest is collected from days other than the targetday, and added to the number of reproductions for the advertisement onthat day, so that the distribution of the advertisement is concentratedon the target day (this process corresponds to operation “3” in FIG. 9).On a day other than the target day, an opening occurs. In order toeliminate overages and openings occurring with respect to theadvertisement slots, expansion/compression adjustments are performedwhile maintaining the ratio of the number of advertisements (thisprocess corresponds to operation “4” in FIG. 9), similar to the case ofthe disallowed day processing.

In the same manner, the calculation method when a disallowed time bandor target time band is specified can also be carried out by processingsimilar to that for the daily calculations. The specific-handicapcoefficients are calculated by the processes shown in FIGS. 10-13.

The “1 Increasing/decreasing adjustment” and “2 Expansion/compressionadjustment” of the “(1) Calculation of the ideal number of allocations”in the disallowed day coefficient calculation flow of FIG. 10 arerespectively performed by the following processes:

-   1. Increasing/decreasing adjustment-   <1> For i=1, 2, 3, . . . , CM_SIZE and d=1, 2, 3, . . . DAYS, the    number of allocations n1(i,d) is determined according to the    following conditions i), ii), and iii):-   i) When advertisement i specifies a disallowance for day d:    n1(i,d)=0-   ii) In the case other than i) and in which advertisement i has a    disallowed day on another day:

${n\; 1\left( {i,d} \right)} = {{n\; 0\left( {i,d} \right)} + {n\; 0\left( {i,d} \right)*{\sum\limits_{j \in {T\; 1}}{0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}}$

T1: Disallowed day set of advertisement i

T2: Date set other than disallowed days of advertisement i

-   iii) For all cases other than i) and ii):    n1(i,d)=n0(i,d)-   2. Expansion/compression adjustment-   <1> For d=1, 2, 3, . . . , DAYS, a expansion/compression ratio    (es(d)) is determined that arranges the advertisement slots for each    advertisement while maintaining the ratios for each advertisement.

$\begin{matrix}{{{es}(d)} = {\left( {{\sum\limits_{i}{n\left( {i,d} \right)}} - {\sum\limits_{k \in {C\; 1}}{n\; 1\left( {k,d} \right)}}} \right)/\left( {{\sum\limits_{i}{n\; 1\left( {i,d} \right)}} - {\sum\limits_{k \in {C\; 1}}{n\; 1\left( {k,d} \right)}}} \right.}} \\{{i = 1},2,3,\ldots\mspace{11mu},{CM\_ SIZE}}\end{matrix}$

C1: Set of advertisement types for which a disallowance occurs on day d

-   <2> For days d=1, 2, 3, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYS,    the ideal number of allocations is determined using the    expansion/compression ratio for each day, in accordance with the    following conditions i) and ii).-   i) When day d of advertisement i is a disallowed day:    n1(i,d)=n1(i,d)-   ii) When day d of advertisement i is not a disallowed day:    n1(i,d)=n1(i,d)*es(d)

The “1 Increasing/decreasing adjustment” and “2 Expansion/compressionadjustment” of “(1) Calculation of ideal number of allocations” in thetarget day coefficient calculation flow of FIG. 11 are respectivelyperformed by the following processes:

-   1. Increasing/decreasing adjustment-   <1> For i=1, 2, 3, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYS, the    number of allocations n1(i,d) is determined in accordance with the    following conditions i), ii), and iii).-   i) When advertisement i specifies a target for day d:    n1(i,d)=n0(i,d)+u(i,d)-   ii) Other cases (in which advertisement i does not specify a target    for day d):

${n\; 1\left( {i,d} \right)} = {{n\; 0\left( {i,d} \right)} - {n\; 0\left( {i,d} \right)*{\sum\limits_{j \in {T\; 1}}{{u\left( {i,j} \right)}/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}$

T1: Date set of target specifications of advertisement i

T2: Date set of days without target specification

where,

${u\left( {i,d} \right)} = \frac{{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)*{\sum\limits_{m}{n\; 0\left( {m,d} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,d} \right)}} - {n\; 0\left( {i,d} \right)} - {{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)}}$m = 1, 2, …  , CM_SIZE

-   2. Expansion/compression adjustment-   <1> For d=1, 2, 3, . . . , DAYS, an expansion/compression ratio is    determined that arranges the advertisement slots for each    advertisement while maintaining the ratios for each advertisement.

${{{es}(d)} = \left( {\sum\limits_{i}{{n\left( {i,d} \right)}/{\sum\limits_{i}{n\; 1\left( {k,d} \right)}}}} \right)},$where i=1, 2, 3, . . . , CM_SIZE

-   <2> For i=1, 2, 3, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYS, the    ideal number of allocations is determined using the    expansion/compression ratio for each day.    n1(i,d)=n1(i,d)*es(d)

The “1 Increasing/decreasing adjustment and exchange adjustment of (1)Calculation of ideal number of allocations” in the category weightcalculation flow shown in FIG. 28 is carried out by the followingprocesses:

-   1. Increasing/decreasing adjustment and exchange adjustment    (increasing/decreasing adjustment method B)-   <1> For each of i=1, 2, 3, . . . , CM_SIZE, when j=1, 2, 3, . . . ,    CATEGORIES, the increasing/decreasing adjustment and exchange    adjustment are performed under the following conditions i) to    determine the number of allocations n1(i,j).-   i) When category j is a target specification of advertisement i:    n1(i,j)=n1(i,j)+u(i,j)

where,

${u\left( {i,j} \right)} = \frac{{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)*{\sum\limits_{m}\;{n\; 0\left( {m,j} \right)}}}{{\sum\limits_{m}\;{n\; 0\left( {m,j} \right)}} - {n\; 0\left( {i,j} \right)} - {{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)}}$m = 1, 2,  …  , CM_SIZE

-   <1>-1 (Exchange adjustment)

For n=1, 2, 3, . . . CATEGORIES, the specified degree ofincrease/decrease is reduced for advertisement i by the amount ofadvertising in other categories, in accordance with the conditions i-1)shown below:

-   i-1) When advertisement i has no target specification for category    n:

${n\; 1\left( {i,n} \right)} = {{n\; 1\left( {i,n} \right)} - {{u\left( {i,j} \right)}*{\sum\limits_{k \in {T\; 1}}{n\; 0{\left( {i,k} \right)/{\sum\limits_{k \in {T\; 2}}{n\; 0\left( {i,k} \right)}}}}}}}$

-   <1>-1 For m=1, 2, . . . , CM_SIZE, the exchange amount is determined    in accordance with the following conditions.

${{ds}\left( {m,n} \right)} = {\left( {{u\left( {i,j} \right)}*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,k} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,k} \right)}}}}}} \right)*n\; 1{\left( {m,j} \right)/{\sum\limits_{k}{n\; 1\left( {k,j} \right)}}}}$k = 1, 2, …  , CM_SIZE

-   i-1-1) (Exceptional processing)

When there is no advertising amount to be exchanged:(n1(m,n)−ds(m,n)<0)ds(m,n)=n1(m,n)*Ds, where Ds=0.9 (arbitrary)

-   <1>-1-2 (Exchange)

For m=1, 2, . . . , CM_SIZE, the amount of advertising isincreased/decreased according to the exchange amount.n1(m,n)=n1(m,n)+ds(m,n)n1(m,j)=n1(m,j)−ds(m,n)

T1: Category set of target specifications of advertisement i

T2: Category set other than target specifications of advertisement i

The “1 Increasing/decreasing processing”; “2 Openings and overage amountcalculation”; and “Slot and remaining number updating” of “(1)Calculation of ideal number of allocations (n′(i,j)) in the categoryweight calculation flow shown in FIG. 29 are performed by the followingprocessing.

-   1. Increasing/decreasing processing-   <1> For each of i=1, 2, 3, . . . , CM_SIZE, when j=1, 2, 3, . . . ,    CATEGORIES, the number of unit allocations is determined in    accordance with the following conditions i) and ii).-   i) When category j is a target specification of advertisement i:    n1(i,j)=n0(i,j)+u(i,j)-   ii) Other cases:

${n\; 1\left( {i,j} \right)} = {{n\; 0\left( {i,j} \right)} - {n\; 0\left( {i,j} \right)*{\sum\limits_{k \in {T\; 1}}{{u\left( {i,k} \right)}/{\sum\limits_{k \in {T\; 2}}{n\; 0\left( {i,k} \right)}}}}}}$

T1: Category set of target specifications of advertisement i

T2: Date set of the category without target specifications ofadvertisement i

where,

${u\left( {i,j} \right)} = \frac{{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)*{\sum\limits_{m}{n\; 0\left( {m,j} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,j} \right)}} - {n\; 0\left( {i,j} \right)} - {{a\left( {i,j} \right)}*n\; 0\left( {i,j} \right)}}$

-   2. Openings and overage amount calculation-   <1> For j=1, 2, 3, . . . , CATEGORIES, the total number of    distributions for each category that was increased/decreased as    shown in 1 is calculated.

$\begin{matrix}{{{s\; 0(j)} = {\sum\limits_{i}{n\; 0\left( {i,j} \right)}}},} \\{{s\; 1(j)} = {\sum\limits_{i}{n\; 1\left( {i,j} \right)}}} \\{{i = 0},1,2,3,\ldots\mspace{11mu},{CM\_ SIZE}}\end{matrix}$

-   <2> For i=0, 1, 2, 3, . . . , CM_SIZE and j=1, 2, 3, . . . ,    CATEGORIES, each value is calculated in accordance with the    following conditions i) and ii).-   i) When a slot overage occurs (s1(j)−s0(j)>0):    Ns(i)=Ns(i)−n1(i,j)*(s0(j)/s1(j))    n0(i,j)=0    n2(i,j)=n2(i,j)+n1(i,j)*(s0(j)/s1(j))-   ii) When there is a slot opening (s0(j)−s1(j)≦0):    Ns(i)=Ns(j)−n1(i,j)    n0(i,j)=(s0(j)−s1(j))*n1(i,j)/s1(j)    n2(i,j)=n1(i,j)-   3. Slot and remaining number of times updating-   <1> For each of i=0, 1, 2, 3, . . . , CM_SIZE, when j=1, 2, 3, . . .    , CATEGORIES, the number of unit allocations is updated.

n 0(i, j) = Ns(i) * ctgy(j)Allctgy//Re-allocationn 0(i, j) = n 0(i, j) + un(i, j)//Add  unit  amount${where},\begin{matrix}{{{allctgy} = {\sum\limits_{j}\;{\sum\limits_{i}{n\; 0\left( {i,j} \right)}}}},{and}} \\{{{ctgy}(j)} = {\sum\limits_{i}{n\; 0\left( {i,j} \right)}}} \\{{i = 0},1,2,3,\ldots\mspace{11mu},{CM\_ SIZE}} \\{{j = 1},2,3,\ldots\mspace{11mu},{CATEGORIES}}\end{matrix}$

In this case, the “1 Increasing/decreasing adjustment” and “2Expansion/compression processing” of “(1) Calculation of ideal number ofallocations” in the disallowed time band coefficient calculation flowshown in FIG. 13 are respectively performed by the following processes:

-   1. Increasing/decreasing adjustment-   <1> For i=1, 2, 3, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYS, the    number of allocations n1(i,d) is determined according to the    following conditions i), ii), and iii):-   i) When advertisement i has a disallowance specification for time    band t:    n1(i,t)=0-   ii) In cased other than i) where advertisement i has a disallowance    specified for another time band:

${n\; 1\left( {i,t} \right)} = {{n\; 0\left( {i,t} \right)} + {n\; 0\left( {i,t} \right)*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}}$

T1: Disallowed time band set of advertisement i

T2: Time band set without the disallowed time band of advertisement i

-   iii) all cases other than i) and ii):    n1(i,t)=n1(i,t)+n0(i,t)-   2. Expansion/compression adjustment-   <1> For t=1, 2, 3, . . . , 24, the expansion/compression rate (es)    that arranges each advertisement slot while maintaining the ratios    for each advertisement is determined.

$\begin{matrix}{{{es}(t)} = {\left( {{\sum\limits_{i}{n\left( {i,t} \right)}} - {\sum\limits_{k \in {C\; 1}}{n\; 1\left( {k,t} \right)}}} \right)/\left( {{\sum\limits_{i}{n\; 1\left( {i,t} \right)}} - {\sum\limits_{k \in {C\; 1}}{n\; 1\left( {k,t} \right)}}} \right)}} \\{{i = 1},2,3,\ldots\mspace{11mu},{CM\_ SIZE}}\end{matrix}$

C1: Set of advertisement types for which a disallowance occurs in thetime band t

-   <2> For i=1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24, the    ideal number of allocations is calculated using the    expansion/compression ratio of each day in accordance with the    conditions i) and ii) shown below:-   i) When the time band t is disallowed for advertisement i:    n1(i,t)=n1(i,t)-   ii) When the time band t is not disallowed for advertisement i:    n1(i,t)=n1(i,t)*es(t)

The “1 Increasing/decreasing adjustment” and “2 Expansion/compressionadjustment” in “(1) Calculation of ideal number of allocations” in thetarget time band coefficient calculation flow shown in FIG. 13 arerespectively performed by the following equations:

-   1. Increasing/decreasing adjustment-   <1> For i=1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24, the    number of allocations n1(i,t) is determined in accordance with the    following conditions i), ii), and iii).-   i) When advertisement i has a target specification for the time band    t:    n1(i,t)=n0(i,t)+u(i,t)-   ii) Other cases (in which time band t is not a target of    advertisement i):

${n\; 1\left( {i,t} \right)} = {{n\; 0\left( {i,t} \right)} + {n\; 0\left( {i,t} \right)*{\sum\limits_{j \in {T\; 1}}{{u\left( {i,j} \right)}/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}$

T1: Target time band set of advertisement i

T2: Time band set without the target time band of advertisement i

where,

${u\left( {i,t} \right)} = \frac{{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)*{\sum\limits_{m}{n\; 0\left( {m,t} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,t} \right)}} - {n\; 0\left( {i,t} \right)} - {{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)}}$m = 1, 2, …  , CM_SIZE

-   2. Slot adjustment processing-   <1> For t=1, 2, 3, . . . , 24, the advertisement slots are arranged    while maintaining the ratios of each advertisement.    es(t)=Σn(i,t)/Σn1(i,t), where i=1, 2, 3, . . . , CM_SIZE-   <2> For i=1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24, the    ideal number of allocations is determined from the    expansion/compression ratio for each day.    n1(i,t)=n1(i,t)*es(t)

In this calculation method, for example, when many advertisements have adisallowance specification, a difference occurs between the total numberof reproductions for the advertisement for each advertisement. However,the processing is extremely simple, so that a feature of this method isthat it needs only a small calculation burden and a simple systemconfiguration.

(Method II)

Next, a different calculation method for adjusting openings and overagesin advertisement slots will be described. This method is summarized inFIG. 12.

This calculation method is the same as method I in terms of performinguniform allocation of disallowances to days or time bands that are notdisallowed. However, rather than performing expansion or compression tosuit slots, this method adjusts the number of reproductions for theadvertisement that correspond to the number added to days other than thedisallowance specification days, by proportionally distributingadvertisements without a disallowance specification for the days thatare not disallowed with the ratio of the number of reproductions for theadvertisement and uniformly extracting from them. This could beequivalent to exchange processing of advertisements with a disallowancespecification and advertisements on other days without a disallowancespecification (CM2 in FIG. 9).

In this method, when there is a large number of disallowances, days ortime bands could occur in which exchange is not possible. Thus, inactual processing it is preferable to establish an exchange limit, suchas exchange of 9/10 of the amount of advertisements.

In method II, however, even if the conditions are the same between datesand advertisements, depending upon the sequence of exchange processing,a slight difference occurs in the number of extractions. However, thismethod comprises very simple processing to eliminate the problemoccurring with method I, where advertisements do not fit inadvertisement slots.

The same type of processing, shown in the bottom part of FIG. 9, canalso be carried out to allocate target specifications. For targeting(emphasizing), exchange processing is performed between the number ofreproductions for the advertisement of advertisements with a targetspecification that has been uniformly procured from days without atarget specification, and the equal number of reproductions for theadvertisement proportionally allocated using the ratio of the number ofeach advertisement after emphasis adjustment on the target day. Thispoint slightly differs from the processing for a disallowancespecification.

The calculation flow for disallowance date coefficients is shown inFIGS. 15-18.

The “1 Increasing/decreasing adjustment and exchange adjustments” of“(1) Calculation of ideal number of allocations” in the disallowancedate coefficient calculation flow shown in FIG. 15 are performed by thefollowing process:

-   1. Increasing/decreasing adjustment and exchange adjustment-   <1> For each of i=1, 2, 3, . . . , CM_SIZE, when d=1, 2, 3, . . . ,    DAYs, in the case of the following condition i),    increasing/decreasing and exchange adjustments are performed to    establish the number of allocations n1(i,d)-   i) When the day d is disallowed for advertisement i    n1(i,d)=0-   <1>-1 (Exchange adjustment)

For n=1, 2, 3, . . . , DAYS, the exchange amount is calculated andexchange adjustment is performed.

-   <1>-1-1 (Exchange amount calculation)

For m=1, 2, . . . , CM_SIZE, the exchange amount (ds) is determined inaccordance with the following conditions i-1) and i-2).

-   i-1) When n≠d and advertisement m is not disallowed on day d:

$\begin{matrix}{{{ds}\left( {m,n} \right)} = \left( {n\; 0\left( {i,d} \right)*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)*n\; 1{\left( {m,n} \right)/}}}}}}} \right.} \\{\sum\limits_{k \in {D\; 1}}{n\; 1\left( {k,n} \right)}}\end{matrix}$

-   i-1-1) (Exceptional processing)

For the case in which the advertising amount to be exchanged isinsufficient:(when n1(m,n)−ds(m,n)<0)ds(m,n)=n1(m,n)*Ds, where Ds=0.9 (arbitrary)

-   i-2) Other cases:    ds(m,n)=0-   <1>-1-2 (Exchange)

For m=1, 2, . . . , CM_SIZE, the advertisement amount is increased ordecreased in accordance with the exchange amount.n1(m,n)=n1(m,n)−ds(m,n)//Source of movementn1(m,n)=n1(m,d)+ds(m,n)//Destination of movementn1(i,n)=n1(m,n)+ds(m,n)//Disallowed advertisement

T1: Disallowed date set for advertisement i

T2: Date set for advertisement i

D1: Set of advertisements without a disallowance specification on day d

where, the “1 Increasing/decreasing adjustment and exchange adjustment”of “(1) Calculation of ideal number of allocations” in the target date:coefficient calculation flow shown in FIG. 16 is performed by thefollowing process:

-   1. Increasing/decreasing adjustment and exchange adjustment    (Increasing/decreasing adjustment method B)-   <1> For i=1, 2, 3, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYs, in    the case of the condition i) shown below, increasing/decreasing    adjustment and exchange adjustment are performed and the number of    allocations n1(i,d) is determined.-   i) When day d is a target date for advertisement i:

n 1(i, d) = n 1(i, d) + u(i, d) ${where},\begin{matrix}{{u\left( {i,d} \right)} = \frac{{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)*{\sum\limits_{m}{n\; 0\left( {m,d} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,d} \right)}} - {n\; 0\left( {i,d} \right)} - {{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)}}} \\{{m = 1},2,\ldots\mspace{11mu},{CM\_ SIZE}}\end{matrix}$

-   <1>-1 (Exchange adjustment)

For n=1, 2, 3, . . . , DAYS, the amount of advertising of advertisementi is reduced on other days using the increase/decrease specification inaccordance with the conditions i-1) shown below:

-   i-1) When the advertisement i does not have a target specification    for day n:

${n\; 1\left( {i,n} \right)} = {{n\; 1\left( {i,n} \right)} - {{u\left( {i,d} \right)}*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}}$

-   <1>-1

For m=1, 2, . . . , CM_SIZE, the exchange amount (ds) is furtherdetermined in accordance with the conditions i-1-1) and i-1-2) shownbelow:

-   i-1-1) When advertisement m is not disallowed on day d:

$\begin{matrix}{{{ds}\left( {m,n} \right)} = {\left( {{u\left( {i,d} \right)}*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}} \right)*n\; 1{\left( {m,d} \right)/}}} \\{\sum\limits_{k \in {D\; 1}}{n\; 1\left( {k,d} \right)}}\end{matrix}$

-   i-1-1-1) (Exceptional processing)

For the case in which the advertisement amount to be exchanged isinsufficient:(n1(m,n)−ds(m,n)<0)ds(m,n)=n1(m,n)*Ds, where Ds=0.9 (arbitrary)

-   i-2) For other cases:    ds(m,n)=0-   <1>-1-2 (Exchange)

For m=1, 2, . . . , CM_SIZE, the advertisement amount is increased ordecreased in accordance with the exchange amount.n1(m,n)=n1(m,n)+ds(m,n)n1(m,d)=n1(m,d)−ds(m,n)

T1: Target-specified date set of an advertisement i

T2: Date set without target specification for advertisement i

D1: Set of advertisements without a disallowance specification on day d

where, the “1 Increasing/decreasing adjustment and exchange adjustment”of “(1) Calculation of ideal number of allocations” in the disallowedtime band coefficient calculation flow shown in FIG. 17 is performed bythe following processing.

-   1. Increasing/decreasing adjustment and exchange adjustment-   <1> For each of i=1, 2, 3, . . . , CM_SIZE, when t=1, 2, 3, . . . ,    24, for the case of the condition i) shown below, increasing or    decreasing adjustment and exchange adjustment are performed to    determine the number of allocations n1(i,t).-   i) When time band t of advertisement i is disallowed:    n1(i,t)=0-   <1>-1 (Exchange adjustment)

For n=1, 2, 3, . . . , 24 the exchange amount is calculated and exchangeadjustment is performed.

-   <1>-1-1 (Exchange amount calculation).

For m=1, 2, . . . , CM_SIZE, the exchange amount (ds) is determined inaccordance with the following condition i-1) and i-2).

-   i-1) When n≠t and the advertisement m does not have a disallowance    on day t:

${{ds}\left( {m,n} \right)} = {\left( {n\; 0\left( {i,t} \right)*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}} \right)*n\; 1{\left( {m,n} \right)/{\sum\limits_{k \in {D\; 1}}{n\; 1\left( {k,n} \right)}}}}$

-   i-1-1) (Exceptional processing)

When there are not enough advertisements to perform disallowedadvertisement exchange:((n1(m,n)−ds(m,n)<0)ds(m,n)=n1(m,n)*Ds, where Ds=0.9 (arbitrary)

-   i-1-2) For other cases:    ds(m,n)=0-   <1>-1-2 (Exchange)

For m=1, 2, . . . , CM_SIZE, the advertisement amount is increased ordecreased in accordance with the exchange amount.n1(m,n)=n1(m,n)−ds(m,n)//Source of movementn1(m,t)=n1(m,t)+ds(m,n)//Destination of movementn1(i,n)=n1(i,n)+ds(m,n)//Disallowed advertisement

T1: Time band set of disallowance specifications for advertisement i

T2: Time band set with no disallowance specification for advertisement i

D1: Set of advertisements without a disallowance specification in timeband t

where, the “1 Increasing/decreasing adjustment and exchange adjustment”of “(1) Calculation of ideal number of allocations” in the target timeband coefficient calculation flow shown in FIG. 18 are performed by thefollowing process:

-   1. Increasing/decreasing adjustment and exchange adjustment    (Increasing/decreasing adjustment method B)-   <1> For i=1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24 for the    case of the condition i) shown below, increasing/decreasing    adjustment and exchange adjustment are performed to determine the    number of allocations n1(i,t).-   i) When time band t is a target for advertisement i:

n 1(i, t) = n 1(i, t) + u(i, t) ${where},\begin{matrix}{{u\left( {i,t} \right)} = \frac{{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)*{\sum\limits_{m}{n\; 0\left( {m,t} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,t} \right)}} - {n\; 0\left( {i,t} \right)} - {{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)}}} \\{{m = 1},2,\ldots\mspace{11mu},{CM\_ SIZE}}\end{matrix}$

-   <1>-1 (Exchange adjustment)

For n=1, 2, 3, . . . , 24, the amount of advertising of advertisement iis reduced in other time bands using the specified amount ofincrease/decrease in accordance with the conditions: i-1) shown below:

-   i-1) When the advertisement i does not have a target specification    for time band t:

${n\; 1\left( {i,n} \right)} = {{n\; 1\left( {i,n} \right)} - {{u\left( {i,t} \right)}*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}}$

-   <1>1-1

For m=1, 2, . . . , CM_SIZE the exchange amount (ds) is furtherdetermined in accordance with the conditions i-1-1) and i-1-2) shownbelow:

-   i-1-1) When the advertisement m is not disallowed in time band t:

${{ds}\left( {m,n} \right)} = {\left( {{u\left( {i,t} \right)}*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}} \right)*n\; 1{\left( {m,t} \right)/{\sum\limits_{k \in {D\; 1}}{n\; 1\left( {k,t} \right)}}}}$

-   i-1-1-1) (Exceptional processing)

When there is not enough advertisement amount to perform exchange:(n1(m,n)−ds(m,n)<0):ds(m,n)=n1(m,n)*Ds, where Ds=0.9 (arbitrary)

-   i-1-2) Other cases:    ds(m,n)=0-   <1>-1-2 (Exchange)

For m=1, 2, . . . , CM_SIZE, the advertisement amount is increased ordecreased according to the exchange amount.n1(m,n)=n1(m,n)+ds(m,n)n1(m,t)=n1(m,t)−ds(m,n)

T1: Time band set with a target specification of an advertisement i

T2: Time band set with no target specification for advertisement i

D1: Set of advertisements without a disallowance specification on timeband t

(Method III)

In yet another method, the case of not fitting into advertisement slots,as in method I, is eliminated, and there is no influence from thesequence of exchange, as in method II. In addition, this method usesre-iterative calculation that has a small amount of calculation andenables enhancement of the emphasis effect, compared with the case ofperforming mathematical programming such as linear programming,described later.

The general allocation processing of method III is shown in FIG. 19. Astep for the adjustment amount of each time is provided. That is, byrepeating adjustment for a fixed amount that is divided by the number oftimes, advertisements with disallowances or the like are graduallyallocated to days or time bands without a disallowance.

Specifically, (1) if the number of adjustment times is set to ten times,for example, 1/10 of the amount of advertisements before adjustment isextracted. The number of adjustment times can be arbitrarily determined.(2) Disallowances are removed, and allocation is made to days other thandisallowed days. All advertisements in slots having openings are movedto the intermediate number of reproductions for the advertisement. Thebreakdown of advertisements in which there is an overage is equivalentto the ratio of the amount of advertisements for each advertisement thatday. Openings (carry-forward slots) and overage amounts (remainingnumber of carry-forwards) exist in each slot, and the totals for eachare equivalent. (4) With respect to the carry-forward slots, the numberof remaining carry-forwards is allocated. (5) 1/10 of the advertisementamount before the adjustment is extracted. (6) A return is made to (2),and the processing ends when the number of repetitions reaches ten. Thenumbers used herein are assigned in common with the numbers in FIG. 19.

Specifically, the disallowed advertisement (CM1) is uniformly allocatedto days that are not disallowed, and the allocated disallowance isdivided into an adjustment amount and an overage amount, whilemaintaining the share for each advertiser.

The portion fitting into the adjustment amount is established as theallocation amount, as is. In order to accelerate the elimination of theoverage amount, it is added to the adjustment amount the next time, andthe same processing is repeated.

Since the overage amount is collected and proportionally allocated againto openings, it is possible to perform allocations that, in contrast tomethod II, are not dependent on the exchange sequence. By using thismethod, it is possible to perform allocations using a finite number ofadjustments, and if the adjustment amount is made small, it is possibleto perform allocation comparable to linear programming. In addition,because greater skewing can occur in allocation ratio than in the degreeof emphasis, this method is attractive to advertisers.

With regard to target specifications, calculations can also be performedin this manner. The specific calculation equations are exemplified inFIGS. 20 to 24.

The “1 Increasing/decreasing adjustment”; “2 Opening and overage amountcalculation”; and “3 Slot and remaining number of times updating” of“(1) Calculation of ideal number of allocations” in the disallowancedate coefficient calculation flow shown in FIG. 20 are performed by thefollowing processes:

-   1. Increasing/decreasing amount processing-   <1> For each of i=1, 2, 3, . . . , CM_SIZE when d=1, 2, 3, . . . ,    DAYS, the unit adjustment amount n1(i,d) is determined in accordance    with the following conditions i), ii), and iii).-   i) When advertisement i has a disallowance specification on day d:    n1(i,d)=0-   ii) For cases other than i) and in which there is a disallowance    specification on another day:

${n\; 1\left( {i,d} \right)} = {{n\; 0\left( {i,d} \right)} + {n\; 0\left( {i,d} \right)*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}}$

T1: Time band set with a disallowance specification of an advertisementi

T2: Time band set with no disallowance specification for advertisement i

-   iii) For all cases other than i) and ii):    n1(i,d)=n0(i,d)-   2. Opening and overage amount calculation-   <1> For d=1, 2, 3, . . . , DAYS, the total unit adjustment amount of    each day that is increased or decreased in the above processing 1 is    calculated.

$\begin{matrix}{{{s\; 0(d)} = {\sum\limits_{i}{0\left( {i,d} \right)}}},} \\{{{s\; 1(d)} = {\sum\limits_{i}{n\; 1\left( {i,d} \right)}}},} \\{{i = 0},1,2,3,{\ldots\mspace{11mu}{CM\_ SIZE}}}\end{matrix}$

-   <2> For each of i=0, 1, 2, 3, . . . , CM_SIZE, when d=1, 2, 3, . . .    , DAYS, values are determined in accordance with the following    conditions i) and ii):-   i) When there is a slot overage (s1(d)−s0(d)>0):    Ns(i)=Ns(i)−n1(i,d)*(s0(d)/s1(d))    n0(i,j)=0    n2(i,d)=n2(i,d)+n1(i,d)*(s0(d)/s1(d))-   ii) When there is a slot opening (s0(d)−s1(d)≧0):    Ns(i)=Ns(d)n1(i,d)    n0(i,d)=(s0(d)−s1(d))*n1(i,d)/s1(d)    n2(i,d)=n2(i,d)+n1(i,d)-   3. Updating slot and number of remaining times-   <1> For each of i=0, 1, 2, . . . , CM_SIZE, when d=1, 2, 3, . . . ,    DAYS, the unit adjustment amount is updated.    n0(i,d)=Ns(i)*day(d)/all day//Re-allocation of remaining number of    times    n0(i,d)=n0(i,d)+un(i,d)//Unit amount addition

where,

$\begin{matrix}{{{all}\mspace{14mu}{day}} = {\sum\limits_{d}\;{\sum\limits_{i}\;{n\; 0\left( {i,d} \right)}}}} \\{{{day}(d)} = {\sum\limits_{i}\;{n\; 0\left( {i,d} \right)}}}\end{matrix}$

-   -   i=0, 1, 2, 3, . . . , CM_SIZE; d=1, 2, 3, . . . , DAYS

“1 Increasing/decreasing adjustment”; “2 Opening and overage amountcalculation”; and “3 Slot and remaining number of times updating” of“(1) Calculation of ideal number of allocations” in the target datecoefficient calculation flow shown in FIG. 21 are performed by thefollowing processes:

-   1. Increasing/decreasing amount processing-   <1> For each of i=1, 2, 3, . . . , CM_SIZE when d=1, 2, 3, . . . ,    DAYS, the unit adjustment amount n1(i,d) is determined in accordance    with the following conditions i) and ii).-   i) When day d is a target date for advertisement i:    n1(i,d)=n0(i,d)+u(i,d)-   ii) Other cases:

${n\; 1\left( {i,d} \right)} = {{n\; 0\left( {i,d} \right)} - {n\; 0\left( {i,d} \right)*{\sum\limits_{j \in {T\; 1}}{{u\left( {i,j} \right)}/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {,j} \right)}}}}}}$

T1: Date set with a disallowance specification for advertisement i

T2: Date set with no disallowance specification for advertisement i

where,

${u\left( {i,d} \right)} = \frac{{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)*{\sum\limits_{m}{n\; 0\left( {m,d} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,d} \right)}} - {n\; 0\left( {i,d} \right)} - {{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)}}$

-   -   m=1, 2, . . . , CM_SIZE

-   2. Opening and overage amount calculation

-   <1> For j=1, 2, 3, . . . , DAYS, the total unit adjustment amount    for each day is calculated that was increased/decreased in    processing 1.

$\begin{matrix}{{{s\; 0(d)} = {\sum\limits_{i}{n\; 0\left( {i,d} \right)}}},} \\{{s\; 1(d)} = {\sum\limits_{I}{n\; 1\left( {i,d} \right)}}}\end{matrix}$i=0, 1, 2, 3, . . . , CM_SIZE

-   <2> For i=0, 1, 2, 3, . . . , CM_SIZE and j=1, 2, 3, . . . , DAYS,    values are determined in accordance with the following conditions i)    and ii):-   i) When there is a slot overage (s1(d)−s0(d)>0):    Ns(i)=Ns(i)−n1(i,d)*(s0(d)/s1(d))    n0(i,j)=0    n2(i,d)=n2(i,d)+n1(i,d)*(s0(d)/s1(d))-   ii) When there is a slot opening (s0(d)−s1(d)≦0)    Ns(i)=Ns(d)−n1(i,d)    n0(i,d)=(s0(d)−s1(d))*n1(i,d)/s1(d)    n2(i,d)=n2(i,d)+n1(i,d)-   3. Slot and remaining number of times updating-   <1> For each of i=0, 1, 2, 3, . . . , CM_SIZE, when j=1, 2, 3, . . .    , DAYS, the unit adjustment amount is updated.    n0(i,d)=Ns(i)*day(d)Allday//Re-allocation    n0(i,d)=n0(i,d)+un(i,d)//Add unit amount

where,

$\begin{matrix}{{{all}\mspace{14mu}{day}} = {\sum\limits_{d}\;{\sum\limits_{i}\;{n\; 0\left( {i,d} \right)}}}} \\{{{day}(d)} = {\sum\limits_{I}\;{n\; 0\left( {i,d} \right)}}} \\{{i = 0},1,2,3,\ldots\mspace{11mu},{{CM\_ SIZE};}} \\{{d = 1},2,3,\ldots\mspace{11mu},{DAYS}}\end{matrix}$

-   -   i=0, 1, 2, 3, . . . , CM_SIZE; d=1, 2, 3, . . . , DAYS

The “1 Increasing/decreasing adjustment”; “2 Opening and overage amountcalculation”; and “Slot and remaining number of times updating” of “(1)Calculation of ideal number of allocations” in the disallowed time bandcoefficient calculation flow shown in FIG. 22 are performed by thefollowing processing, respectively.

-   1. Increasing/decreasing processing-   <1> For each of i=1, 2, 3, . . . , CM_SIZE, when j=1, 2, 3, . . . ,    24, the unit adjustment amount n1(i,t) is calculated in accordance    with the following conditions i) and ii).-   i) When time t is a disallowance specification of advertisement i:    n1(i,t)=0-   ii) For cases other than (i) and in which the advertisement i has a    disallowance specification at another time band:

${n\; 1\left( {i,t} \right)} = {{n\; 0\left( {i,t} \right)} + {n\; 0\left( {i,t} \right)*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{J \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}}$

T1: Target time band set of advertisement i

T2: Time band set without the target time band of advertisement i

-   iii) For cases other than i) and ii):    n1(i,t)=n0(i,t)-   2. Opening and overage calculation-   <1> For t=1, 2, 3, . . . , 24, the total unit adjustment amount of    each day that is decreased or increased as noted in 1 is calculated.

$\begin{matrix}{{{s\; 0(d)} = {\sum\limits_{i}{n\; 0\left( {i,t} \right)}}},} \\{{{s\; 1(d)} = {\sum\limits_{I}{n\; 1\left( {i,t} \right)}}},{where}} \\{{i = 0},1,2,3,\ldots\mspace{11mu},24}\end{matrix}$where i=0, 1, 2, 3, . . . , 24

-   <2> For each of i=0, 1, 2, 3, . . . , CM_SIZE, when t=1, 2, 3, . . .    , 24, values are determined in accordance with the following    conditions i) and ii):-   i) When there is a slot overage (s1(t)−s0(t)>0):    Ns(i)=Ns(i)−n1(i,t)*(s0(t)/s1(t))    n0(i,j)=0    n2(i,t)=n2(i,t)+n1(i,t)*(s0(t)/s1(t))-   ii) When there is a slot opening (s0 (t)−s1(t)≦0):    Ns(i)=Ns(t)−n1(i,t)    n0(i,t)=(s0(t)−s1(t))*n1(i,t)/s1(t)    n2(i,t)=n2(i,t)+n1(i,t)-   3. Updating slot and number of remaining times-   <1> For each of i=0, 1, 2, 3, . . . , CM_SIZE, when t=1, 2, 3, . . .    , 24, the unit adjustment amount is updated.    n0(i,t)=Ns(i)*time(t)/all time//Re-allocation    n0(i,t)=N0(i,t)+un(i,d)//Unit amount addition

where,

$\begin{matrix}{{{all}\mspace{14mu}{time}} = {\sum\limits_{t}\;{\sum\limits_{i}\;{n\; 0\left( {i,t} \right)}}}} \\{{{time}(t)} = {\sum\limits_{i}\;{n\; 0\left( {i,t} \right)}}} \\{{i = 0},1,2,3,\ldots\mspace{11mu},{{CM\_ SIZE}\mspace{14mu}{and}}} \\{{t = 1},2,3,\ldots\mspace{11mu},24}\end{matrix}$i=0, 1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24

The “1 Increasing/decreasing adjustment”; “2 Opening and overage amountcalculation”; and “3 Slot and remaining number of times updating” of“(1) Calculation of ideal number of allocations” in the target time bandcoefficient calculation flow shown in FIG. 23 are performed by thefollowing processes:

-   1. Increasing/decreasing amount processing-   <1> For each of i=1, 2, 3, . . . , CM_SIZE when t=1, 2, 3, . . . ,    24, the unit adjustment amount n1(i,t) is determined in accordance    with the following conditions i) and ii):-   i) When time t is a target time band for advertisement i:    n1(i,t)=n0(i,t)+u(i,t)-   ii) For other cases:

${n\; 1\left( {i,t} \right)} = {{n\; 0\left( {i,t} \right)} - {n\; 0\left( {i,t} \right)*{\sum\limits_{j \in {T\; 1}}{{u\left( {i,t} \right)}/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}$

T1: Time band set with a target specification for advertisement i

T2: Time band set with no target specification for advertisement i

where,

${u\left( {i,t} \right)} = \frac{{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)*{\sum\limits_{m}{n\; 0\left( {m,t} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,t} \right)}} - {n\; 0\left( {i,t} \right)} - {{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)}}$m = 1, 2, …  , CM_SIZE

-   -   m=1, 2, . . . , CM_SIZE

-   2. Opening and overage amount calculation

-   <1> For j=1, 2, 3, . . . , 24, calculation is done of the total unit    adjustment amount for each time band that was increased/decreased in    accordance with the above processing 1.

$\begin{matrix}{{{s\; 0(d)} = {\sum\limits_{i}{n\; 0\left( {i,t} \right)}}},} \\{{s\; 1(t)} = {\sum\limits_{i}{n\; 1\left( {i,t} \right)}}} \\{{t = 0},1,2,3,\ldots\mspace{11mu},24}\end{matrix}$t=0, 1, 2, 3, . . . , 24

-   <2> For i=0, 1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24,    values are calculated in accordance with the following conditions i)    and ii):-   i) Overage (s1(t)−s0(t)>0):    Ns(i)=Ns(i)−n1(i,t)*(s0(t)/s1(t))    n0(i,j)=0    n2(i,t)=n2(i,t)+n1(i,t)*(s0(t)/s1(t))-   ii) Opening (s1(t)−s0(t)≦s0):    Ns(i)=Ns(t)−n1(i,t)    n0(i,t)=(s0(t)−s1(t))*n1(i,t)/s1(t)    n2(i,t)=n2(i,t)+n1(i,t):-   3. Updating slot and remaining number of times-   <1> For each of i=0, 1, 2, 3, . . . , CM_SIZE, when t=1, 2, 3, . . .    , 24, the unit adjustment amount is updated.    n0(i,t)=Ns(i)*time(t)Alltime//Re-allocation    n0(i,t)=n0(i,t)+un(i,t)//Add unit amount

where,

$\begin{matrix}{{{{all}\mspace{14mu}{time}} = {\sum\limits_{t}\;{\sum\limits_{i}\;{n\; 0\left( {i,t} \right)}}}},} \\{{{time}(t)} = {\sum\limits_{i}\;{n\; 0\left( {i,t} \right)}}} \\{{{i = 0},1,2,3,\ldots\mspace{11mu},{{CM\_ SIZE};}}\mspace{11mu}} \\{{t = 1},2,3,\ldots\mspace{11mu},24}\end{matrix}$

-   -   i=0, 1, 2, 3, . . . , CM_SIZE; t=1, 2, 3, . . . , 24        (Method IV)

This method is one that uses linear programming to determine an optimumvalue in order to achieve optimum allocation, and the following aretarget functions, specific equations and the like thereof.

Disallowance Date Coefficient Calculation

(Pre-Conditions)

CM_SIZE: Number of advertisements

DAYS: Planned time period

a(i,d): Disallowance specification information

n0(i,d): Initially allocated number of reproductions for theadvertisement

-   1. Calculation of initially allocated number of reproductions for    the advertisement

$\begin{matrix}{{n\; 0\left( {i,t} \right)} = {{N(i)} \times {log\_ day}{(d)/{\sum\limits_{k}{{log\_ day}(d)}}}}} \\{{k = 1},2,\ldots\mspace{11mu},{DAYS}}\end{matrix}$

k=1, 2, . . . , DAYS

log_day(k): Number of distribution demands for each time band

N(i): Remaining-number of distributions

-   2. For i=0, 1, 2, . . . , CM SIZE and d=1, 2, 3, . . . , DAYS:-   i) When day d is disallowed for advertisement i:    n1(i,d)=0-   ii) For cases other than i) where another day has a disallowance    specification:

${n\; 1\left( {i,d} \right)} = {{n\; 0\left( {i,d} \right)} + {n\; 0\left( {i,d} \right)*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,j} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}}$

T1: Time band set with target specifications for advertisement i

T2: Time band set with no target specification for advertisement i

-   iii) For cases other than i) and ii):    n1(i,d)=0(i,d)-   3. Search for optimum value (n2(i,d))

Mathematical programming is used to determine a combination of n2(i,d)that minimizes the target function Z shown below:

Target Function:

$Z = {{\sum\limits_{i,d}\left\{ {{K\left( {i,d} \right)} \times {\frac{{n\; 1\left( {i,d} \right)} - {n\; 2\left( {i,d} \right)}}{n\; 1\left( {i,d} \right)}}} \right\}}->\min}$

-   -   i=1, 2, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYS        K(i,j)=1        Restriction Conditions:

${\sum\limits_{d}{n\; 2\left( {i,d} \right)}} = {\sum\limits_{d}{n\; 0\left( {i,d} \right)}}$${\sum\limits_{i}{n\; 2\left( {i,d} \right)}} = {\sum\limits_{i}{n\; 0\left( {i,d} \right)}}$

-   -   i=1, 2, 3, . . . , CM_SIZE    -   d=1, 2, 3, . . . , DAYS        n2(i,d)=0 (if a(i,d)=0)//Disallowed day variable ignored

-   4. Calculation of weight function (A)

${A\left( {i,d} \right)} = \left\{ \begin{matrix}{n\; 2{\left( {i,d} \right)/{N(i)}}} & {\left( {{{when}\mspace{14mu} d} = 1} \right)} \\{n\; 2{\left( {i,d} \right)/\left( {{N(i)} - {\sum\limits_{j = 1}^{d - 1}{n\; 2\left( {i,j} \right)}}} \right)}} & {\left( {d \neq 1} \right)}\end{matrix} \right.$Target Date Coefficient Calculation

(Pre-Conditions)

CM_SIZE: Number of advertisements

DAYS: Planned time period

a(i,d): Increase/decrease specification information

n0(i,d): Initially allocated number of distributions

-   1. Initially allocated number of reproductions for the advertisement    calculation    n0(i,d)=A(i,d)×N(i)

A(i,d): Disallowance date coefficient

N(i): Remaining number of distributions

-   2. Ideal value (n1(i,d)) determination

For i=0, 1, 2, 3, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYS:

-   i) When day d is a target date for advertisement i:    n1(i,d)=n0(i,d)+u(i,d)-   ii) For other cases (in which day d is not a target date for    advertisement i):

${n\; 1\left( {i,d} \right)} = {{n\; 0\left( {i,d} \right)} - {n\; 0\left( {i,d} \right)*{\sum\limits_{j \in {T\; 1}}{{u\left( {i,d} \right)}/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}$

T1: Set of target time bands for advertisement i

T2: Set of target time bands without the target specifications ofadvertisement i

where,

${u\left( {i,d} \right)} = \frac{{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)*{\sum\limits_{m}{n\; 0\left( {m,d} \right)}}}{{\sum\limits_{m}{n\; 0\left( {m,d} \right)}} - {n\; 0\left( {i,d} \right)} - {{a\left( {i,d} \right)}*n\; 0\left( {i,d} \right)}}$

-   -   m=1, 2, . . . , CM_SIZE

-   3. Search for optimum value (n2(i,d))

Mathematical programming is used to determine a combination of n2(i,d)that minimizes the target function Z shown below:

Target function:

$Z = {{\sum\limits_{i,d}\left\{ {{K\left( {i,d} \right)} \times {\frac{{n\; 1\left( {i,d} \right)} - {n\; 2\left( {i,d} \right)}}{n\; 1\left( {i,d} \right)}}} \right\}}->\min}$

-   -   i=1, 2, . . . , CM_SIZE and d=1, 2, 3, . . . , DAYS

${K\left( {i,j} \right)} = \left\{ \begin{matrix}1 & {\left( {{{if}\mspace{14mu}{a\left( {i,d} \right)}} = 0} \right)//{{No}\mspace{14mu}{target}\mspace{14mu}{specification}}} \\k & {{({otherwise})//{{Target}\mspace{14mu}{specification}\mspace{14mu}{exists}}};} \\\; & {\mspace{115mu}{k\mspace{14mu}{is}\mspace{14mu}{arbitrary}\mspace{14mu}{{constant}.}}}\end{matrix} \right.$Restriction Conditions:

${\sum\limits_{d}{n\; 2\left( {i,d} \right)}} = {\sum\limits_{d}{n\; 0\left( {i,d} \right)}}$${\sum\limits_{i}{n\; 2\left( {i,d} \right)}} = {\sum\limits_{i}{n\; 0\left( {i,d} \right)}}$

-   -   i=1, 2, 3, . . . , CM_SIZE    -   d=1, 2, 3, . . . , DAYS.

-   4. Calculation of weight function (A)

${w\left( {i,d} \right)} = \left\{ \begin{matrix}{n\; 2{\left( {i,d} \right)/{N(i)}}} & {\left( {{{when}\mspace{14mu} d} = 1} \right)} \\{n\; 2{\left( {i,d} \right)/\left( {{N(i)} - {\sum\limits_{j = 1}^{d - 1}{n\; 2\left( {i,j} \right)}}} \right)}} & {\left( {d \neq 1} \right)}\end{matrix} \right.$B(i,d)=w(i,d)/A(i,d)

Disallowance Time Band Coefficient Calculation

(Pre-Conditions)

CM_SIZE: Number of advertisements

a(i,t): Disallowance specification information

n0(i,t): Initially allocated number of reproductions for theadvertisement

-   1. Calculation of initially allocated number of reproductions for    the advertisement    n0(i,t)=A(i,d)×B(i,d)×N(i)×log_time(t)/Σ log_time(k)

k=1, 2, . . . , 24

A(i,d): Disallowance date coefficient

N(i): Remaining number of distributions

log_time(k): Number of distribution demands for each time band

B(i,d): Target date coefficient

-   2. Ideal value (n1(i,t)) determination

For i=0, 1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24:

-   i) When time t is disallowed for advertisement i:    n1(i,t)=0-   ii) For cases other than i) where another time band has a    disallowance:

${n\; 1\left( {i,t} \right)} = {{n\; 0\left( {i,t} \right)} + {n\; 0\left( {i,t} \right)*{\sum\limits_{j \in {T\; 1}}{n\; 0{\left( {i,t} \right)/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,t} \right)}}}}}}}$

T1: Set of target time bands for advertisement i

T2: Set of target time bands without the target specifications ofadvertisement i

-   iii) All cases other than i) or ii):    n1(i,t)=0(i,t)-   3. Search for optimum value (n2(i,t))

Mathematical programming is used to determine a combination of n2(i,t)that minimizes the target function Z shown below:

Target Function:

$Z = {{\sum\limits_{i,t}\left\{ {{K\left( {i,t} \right)} \times {\frac{{n\; 1\left( {i,t} \right)} - {n\; 2\left( {i,t} \right)}}{n\; 1\left( {i,t} \right)}}} \right\}}->\min}$

i=1, 2, . . . , CM_SIZE; t=1, 2, 3, . . . , 24K(i,j)=1Restriction Conditions:

${\sum\limits_{t}{n\; 2\left( {i,t} \right)}} = {\sum\limits_{t}{n\; 0\left( {i,t} \right)}}$${\sum\limits_{i}{n\; 2\left( {i,t} \right)}} = {\sum\limits_{i}{n\; 0\left( {i,t} \right)}}$

-   -   i=1, 2, 3, . . . , CM_SIZE; t=1, 2, 3, . . . , 24        n2(i,t)=0 (if a(i,t)==0)//Disallowance time band variable        ignored

-   4. Disallowance time band coefficient (C) calculation    w(i,t)=n2(i,t)/N(i)    C(i,t)=w(i,t)/(A(i,d)*B(i,d))    Target Time Band Coefficient Calculation

(Pre-Conditions)

CM_SIZE: Number of advertisements

a(i,t): Increase/decrease specification information

n0(i,t): Initially allocated number of reproductions for theadvertisement

-   1. Calculation of initially allocated number of reproductions for    the advertisement    n0(i,t)=A(i,d)×B(i,d)×C(i,t)×N(i)

A(i,d): Disallowance date coefficient

B(i,d): Target date coefficient

C(i,t): Disallowance time band coefficient

N(i): Remaining number of distributions

-   2. Ideal value (n1(i,t)) determination

For i=0, 1, 2, 3, . . . , CM_SIZE and t=1, 2, 3, . . . , 24:

-   i) When time t is a target time band for advertisement i:    n1(i,t)=n0(i,t)+u(i,t)-   ii) For other cases (in which time t of advertisement i is not a    target time band)

${n\; 1\left( {i,t} \right)} = {{n\; 0\left( {i,t} \right)} - {n\; 0\left( {i,t} \right)*{\sum\limits_{j \in {T\; 1}}{{u\left( {i,j} \right)}/{\sum\limits_{j \in {T\; 2}}{n\; 0\left( {i,j} \right)}}}}}}$

T1: Set of target time bands for advertisement i

T2: Set of target time bands without the target specifications ofadvertisement i

where,

${u\left( {i,t} \right)} = \frac{{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)*{\sum\limits_{m}{n\; 0\left( {m,t} \right)}}}{\begin{matrix}{{\sum\limits_{m}{n\; 0\left( {m,t} \right)}} - {n\; 0\left( {i,t} \right)} - {{a\left( {i,t} \right)}*n\; 0\left( {i,t} \right)}} \\{{m = 1},2,\ldots\mspace{11mu},{CM\_ SIZE}}\end{matrix}}$

-   3. Search for optimum value (n2(i,t))

Mathematical programming is used to determine a combination of n2(i,d)that minimizes the target function Z shown below:

Target Function:

$Z = {{\sum\limits_{i,t}\left\{ {{K\left( {i,t} \right)} \times {\frac{{n\; 1\left( {i,t} \right)} - {n\; 2\left( {i,t} \right)}}{n\; 1\left( {i,t} \right)}}} \right\}}->\min}$

-   -   i=1, 2, . . . , CM_SIZE and t=1, 2, 3, . . . , 24

${K\left( {i,j} \right)} = \left\{ {\begin{matrix}{{1\left( {{{if}\mspace{14mu}{a\left( {i,j} \right)}} = 0} \right)}//{{No}\mspace{14mu}{target}\mspace{14mu}{specification}}} \\{{k({otherwise})}//{{Target}\mspace{14mu}{specification}}} \\{\mspace{166mu}{{arbitrary}\mspace{14mu}{constant}\mspace{14mu} k}}\end{matrix};} \right.$Restriction Conditions:

${\sum\limits_{t}{n\; 2\left( {i,t} \right)}} = {\sum\limits_{t}{n\; 0\left( {i,t} \right)}}$${\sum\limits_{t}{n\; 2\left( {i,t} \right)}} = {\sum\limits_{t}{n\; 0\left( {i,t} \right)}}$

-   -   i=1, 2, 3, . . . , CM_SIZE    -   t=1, 2, 3, . . . , 24

-   4. Target time band coefficient (D)    w(i,t)=n2(i,t)/N(i)    D(i,t)=w(i,t)/(A(i,d)*B(i,d)*C(i,t))

Because there is an increase in the amount of calculation accompanyingan increase in the number of advertisements and the like that arehandled, there is an increase in the burden placed on hardware. However,with improved hardware performance, there is an improvement in itspractical usefulness, enabling optimum distribution that in line with adegree of emphasis.

(Increase/Decrease Adjustment Method (Calculation of Added Amount))

What follows is a supplementary description of the method for derivingthe target coefficient, which is the amount of advertisements to beadded to the number of reproductions for the advertisement with targetspecification in the case of targeting (emphasis) being applied tocategories, days, or time bands by the advertiser (refer to FIG. 24).

In general, the added amount is derived by using method B shown in FIG.25. Specifically, from the size of the slot before adjustment the addedamount is determined so that the increase/decrease ratio determined bythe increase/decrease specification is achieved after the addition ismade. This added amount is the product of the ratio given by basiccoefficient, relative to the total advertising amount for day d beforeadjustment, and the advertising amount.

The added amount, however, can be defined as being derived by method A,shown in FIG. 25, because this is no more than an issue of thedefinition of “emphasis”. That is, this method is one whereby the basiccoefficient with respect to the absolute number of reproductions for theadvertisement of an advertisement is used to determine the ratio ofincrease or decrease, and this ratio is taken as the added amount.

Additionally, as shown by the method A+B of FIG. 26, derivation ispossible from this combination. That is, after doing the adding usingthe method A, method B is used to derive the final adding. By using thismethod, when there is both positive and negative adjustment, theexpansion of the amount of increase or decrease is smaller than thatusing the method B.

In the present invention targeting processing can be performed using theadded amount by any of these definitions.

In the case of implementing a distribution system of the presentinvention, if the actual number of distribution demands exceeds theexpected number of distributions, openings occur in the “advertisinglist”; meaning that the “number of planned distributions” becomes zero,after which the extraction probability of that advertisement becomeszero, resulting in the possibility of a lost business opportunity.

Given the above, the present invention comprises an embodiment in which,using the following function ƒ(x) rather than the actual number of timesbase as the number of planned distributions (x), the planned number ofdistributions does not become zero.f(x)=x+α×x ₀,

where α is set so as to constantly adjust to the size of the advertisinglist, this being (remaining number of planned distributions of alladvertisements−remaining number of planned distributions for aparticular advertisement)/(overall number of planned distributions); andx₀ is the number of planned distributions and non-zero value.

The “planned number of distributions” function ƒ(x) is not limited tothe above-noted function, and is allowed as long as it approximates theactual number of planned distributions and is not zero.

In addition, the “planned number of distributions” function ƒ(x) is notlimited to the above-noted function, and the following functions can beenvisioned.f(x)=α×x+(1−α)×x ₀,

where α is a constant 0 or greater and 1.0 or less, and x₀ is the numberof reproductions for the advertisement that is not 0.f(x)=x+αx ₀,

where α is a constant that is 0 or greater and x₀ is the number ofreproductions for the advertisement that is not 0.

In the case of using such planned number of distribution functions f(x),the number of reproductions for the advertisement of each advertisementcan be greater than the planned number of distributions.

Therefore, as a result, when there is a large difference between theplanned number of distributions and the number of actual reproductionsfor the advertisement, rather than a form of distributions in which the“initial number of reproductions for the advertisement” is given highestpriority, emphasis is placed on the advertising ratio of eachadvertisement, where there is uniform distribution in terms of thedifferences in distribution opportunities between advertisements.

By adopting such functions, it is possible to not only avoid the dangerof the advertising list losing opportunities, but also to eliminateinstability in extraction probability when the planned number ofdistributions in the advertising list becomes small.

Additionally, a practical solution for the problem of the planned numberof distributions becoming zero is to contemplate such a conditionbeforehand, and prepare an advertising list for the purpose ofscrambling. Furthermore, when the planned number of distributions ofonly a part of the advertisements is zero, or close to zero, extractioncan be performed from the scrambling advertising list at a predeterminedfrequency.

By doing this, it is possible to suppress the concentrated advertisementof one and the same advertisement.

(Coefficient of Slot Size in Seconds)

A practical problem that exists in actual distribution using the presentinvention is that, because of mixing of various advertisement slotpatterns (size of an advertisement slot for one time) and length(seconds) of the advertisement material, in control of the extractionprobability, there is a further need for compensation by furthercontrolling the coefficient of slot size in seconds.

The following three methods can be specific solutions for this problem.

-   (1) Method of Using a Decision Tree (Part 1)

In this case, the advertisement slot patterns and advertisement materiallengths are finite in number. Hence even though the number ofcombinations thereof could be huge, it is still finite. Thus it is alsopossible to pre-prepare a coefficient of slot size in seconds thatpre-adjusts the advertisement probability.

Given the above, one specific method can be envisioned for solving thisproblem wherein, as exemplified in FIG. 30, a weight coefficient(coefficient of slot size in seconds) is prepared beforehand from theselection probability and the change ratio, by assuming a decision treeof all combinations. The method for solving this problem, however, isnot restricted to this method.

The general processing flow is as follows.

N(m): Number of advertisement times for each category

len(m): The length of an advertisement content (second)

Flame: 13 slot patterns

w_flame(m, 13): Coefficient of slot size in seconds

-   1) The selection probability P0(i) is calculated based on the number    of advertisement times for each viewer category    P0(i)=N(i)/ΣN(i)-   2) Decision tree generation-   (a) Setting initial values    rem=Flame(k)//Remaining slot=slot pattern    par_id//No parent advertisement (start)-   (b) calc_tree (rem, par_id)//Branch generation (remaining slot,    parent advertisement)

Check whether the advertisement i (c_id(i)) satisfies the followingconditions (for i=1, 2, . . . , n)(i) len(i)>=rem//Advertisement content length>=number of secondscoefficient(ii) par _(—) id< >c _(—) id(i)//Child is different advertisement fromparent (continuity check)

(Advertisement i corresponds) calc_tree (rem−len(i), c_(i)//Remainingslot; update parent and call processing (b) (return)

(No corresponding advertisement) End of branch

-   3) Calculate the occurrence rate P1(i) for slot k, using the    decision tree of 2).-   4) For each advertisement, the change ratio s(i) of P0(i) and P1(i)    is determined.    S(i)=P1(i)/P0(i)-   5) Determine the maximum common multiple max of the change ratio    s(xi).-   6) Calculate the handicap coefficient for (flame(k))    w_flame(i,k)=max/s(i)-   7) Change the slot pattern (flame(k)) and perform steps 2) to 6).

(k=1, 2, . . . , 13)

The decision tree of FIG. 30 is an example in which A is a 30-secondadvertisement, the other advertisements B, C, and D are 15-secondadvertisements, and a 30-second slot is filled.

-   (2) Method of Using a Decision Tree (Part 2)

A method that can be used to utilize the decision tree of (1) is to fillthe individual advertisement slots by determining the expected valuethat selects each advertisement via a decision tree path on first timeextraction only, applying weight based on individual expected values,but not in accordance with the difference in number of advertisementseconds (that is, in proportion to the planned number of distributions),and performing usual random extractions at the next extraction steps.

FIG. 31 is a drawing describing the concept of a decision tree, andweight for 15-second and 30-second advertisements with respect to a60-second slot.

The difference between this method and the above-described method (1) isthat only when the first random extraction is done with respect to theindividual 60-second slots, an operation is performed to apply handicapsthat consider subsequent variations.

-   (3) Method of Expressing the Slot Size in Seconds as an Expected    Value and Specifying the Number of Extraction Times

By determining the number of extraction times such that the expectedvalue of the overall time period of advertising is the same as thenumber of advertisement slot seconds, it is possible to maintain, onaverage, the advertising ratio for each advertisement, regardless of theadvertisement length. In the case of individual advertisement slots,however, there will be a slight deviance relative to the 60-second slot,as noted below.

<Step 1>

Determine the expected values of the number of advertisement secondswithin the advertising list.

<Step 2>

Calculate the number of extraction times so that the slot number ofseconds is the expected value, based on the slot size in seconds and theexpected value of the number of advertisement seconds.

For example, consider an example of the number of advertisement slotseconds of 60 seconds, an advertisement A (15 seconds, 100 times),advertisement B (15 seconds, 100 times), advertisement C (30 seconds,100 times), and advertisement D (60 seconds, 100 times).

First, as step 1, the expected value E of the number of advertisementseconds at one extraction time is determined. That is, the overall totalof the products of the number of seconds for each advertisement and itsextraction probability is taken. The result in this example will be 30seconds. Since this expected value E of the number of advertisementseconds is the average time which can fill in an advertisement slot foreach extraction time, stated differently there are 400 times worth of a30-second advertisement.

As step 2 the number of extraction times is determined that is requiredto fill the number of advertisement slot seconds. When the number ofadvertisement slot seconds E is 60 seconds, the number of extractionswould be two. That is, by placing the 30-second advertisement twice, the60-second advertisement slot is filled.

Therefore, if two extractions are made for each advertisement slot,although midway there will be fluctuation in the time length foradvertisements in individual advertisement slots, the minimum being 30seconds and the maximum being 120 seconds, the final totals willindicate a distribution result in which the specified number ofadvertisement slot seconds is the expected value, thereby enabling theplanned advertisement slots to be filled.

Thus, for advertisements 1, 2, . . . , m, . . . , M, if the length ofthe content of advertisement m is len(m) and the number of advertisementtimes in each category for advertisement m is N(m), the expected value Eof the length of the advertisement content is given by the followingequation:E=(len(n)×N(m))/ΣN(m)

Thus, if the specified number of advertisement slot seconds is Flame,the number of extractions of interest can be determined asFlame×(1/E).

Although the number of extraction times determined in step 2 may not bean integer number of times, it is possible to round the number of timesupward or downward.

-   (4) Method of Specifying the Slot Size in Seconds and Extraction    Times

Step 1:

By the above-noted method (3), calculate the number of extraction timessuch that the slot size in seconds is the expected value.

Step 2:

By the above-noted method (1) or (2), determine the decision tree forthe number of extraction times of step 1.

Step 3:

In the decision tree generated by step 2, arrange the branches that areoutside the allowable limit of the slot size in seconds.

In the above the “allowable limit” is as follows:

Slot size in seconds−Δ<advertisement length (sum of the number ofseconds of advertisements of each branch)<slot size in seconds+Δ

(The sizes of −Δ and +Δ are not necessarily the same.)

A merit of this method is that processing is simplified because thenumber of extractions is small and it is possible to reduce division ofthe branches of the decision tree. Furthermore, the range of variationin the slot size in seconds E can be controlled.

As an example, consider a case in which the slot size in seconds is 60seconds, which includes advertisement A (15 seconds, 100 times),advertisement B (15 seconds, 100 times), advertisement C (30 seconds,100 times), and advertisement D (60 seconds, 100 times).

In the illustrated case, the slot size in seconds range is −Δ1=15seconds and +Δ2=30 seconds, this being a time range of 45 to 90 seconds.This range is that indicated by the broken line in FIG. 32( a).

The probability distribution in this case is noted in FIG. 32( b).

Step 1: Specified number of times=2

Step 2: The branches of the first time 15-second advertisement and thesecond time 15-second advertisement outside the broken line, and thefirst time 60-second advertisement and second time 60-secondadvertisement branches are arranged. If this extraction pattern arises,that extraction would be ignored and extraction would be performedagain.

(On-Line Processing)

In the advertisement insertion system 7, a pre-allocated advertisinglist 15-2, generated via the above-noted process and allocated for eachsales unit, is received from an advertisement advertising server 4, andpreparation for on-line processing is achieved.

An advertisement information request and viewer information are receivedfrom a viewer terminal 2 that is playing back program video content, andadvertisement information responsive to the sales unit determined by theadvertisement information and the viewer information is distributed tothe viewer terminal 2. After this, the processing flow is as shown inFIG. 33.

As described above, in the pre-distributed advertising list uploadingprocess 8, the pre-allocated monthly advertising list exemplified inFIG. 34 is received and stored, which is generated by the advertisementadvertising server.

In the allowance checked advertising list generation process 9, theexistence of authentication for each of the advertisement originals andthe advertisement data, and the presence in the advertising server 1 areconfirmed with respect to the pre-allocated advertising list 15-2 thatwas captured in the advertising list uploading process 8. The allowedtime period is also checked based on allowance information. Allowanceinformation is verified by acquiring the allowance information of theadvertisement content from the allowance management server 16. Thechecked advertising list is then stored as a pre-checked advertisinglist in a database. An example of a pre-checked advertising list isshown in FIG. 35.

In the allowance checked advertising list generation process 9, a checkof the advertisement originals and the advertisement data allowanceperiod of time are performed with respect to the pre-checked advertisinglist as well. Thus, even if the allowance information or advertisementdata or the like is changed after the advertising list uploaded, thecontent thereof is reflected automatically.

The allowance checked advertising list generation processing ispreferably launched daily.

In the weight coefficient calculation process 10, the handicapcoefficient is calculated for each pre-checked advertising list. In thedistribution list generation process 13, advertisement selection isperformed by random extraction probability based on the number ofreproductions for the advertisement for each advertisement included inthe pre-checked advertising list.

As described above, control is possible such that the delay in progressof advertisements with disallowances is eliminated by increasing theamount of advertisements that could not be distributed because ofdisallowed days or time bands on other days or time bands. In addition,it is possible to distribute the advertisements on the specified days ortime bands. Furthermore, similar treatment can be applied, for example,when the occurrence probability reduces relative to the slot size inseconds due to the difference of advertisement content seconds.

In addition, as a result, the calculated handicap coefficients areretained in the checked advertising list. This weight coefficientcalculation process is preferably launched daily.

When there is a specific request from a viewer on the viewer terminal 2,request acceptance 11 also receives an advertisement request from theviewer terminal 2, and viewer information at the same time.

(Checking Processes)

In the various checking processes 12, a checked advertising list that islinked by an advertisement request and viewer information passed by therequest acceptance section 11 is acquired from a database. The allowanceconditions, usage conditions, and advertisement slot conditions arepreferably included within the advertisement request. In addition, it ispossible to acquire detailed information from viewer information, suchas region and age, by accessing the viewer information database 15-1using a viewer code.

Information comprised in the advertisement request and viewerinformation is as follows: First, the advertisement request usuallycomprises usage information including allowance conditions such as thenetwork, region, age, date, and time band; usage conditions such asformat, number of pixels, and bit rate; and advertisement slotconditions such as the distribution provider, advertisement slot size inseconds, advertising list class, program content code, and slot number.Viewer information usually comprises items such as age, region, viewercategory, past actions and behavior, viewer code, and player ID.

In accordance with narrowing conditions, such as advertisement slot sizein seconds, time band, and network, narrowing is carried out from theoverall advertisement originals within the checked advertising list, toselect only the target advertisement originals.

A specific method for checking, based on the time of a viewer requestand whether the time was a disallowed time band is, as described above,a method wherein the disallowance time band coefficients, which are oneof the handicap coefficients, are all made zero values. Thus the requestis substantially removed from the subject in the random extraction.

The distribution list generation process 13 is preferably configuredsuch that the advertisement originals distributed last time, and theadvertisement originals for which the frequency is excessive, arefurther removed from the advertisement originals after narrowing withinthe checked advertising list. The frequency is the number ofdistributions of an advertisement original for each viewer, and isinformation that is held within the viewer information. In thedistribution list generation process 13, extraction from theadvertisement originals narrowed within the checked advertising list isperformed with probabilities that are proportional to values that arethe product of the number of reproductions for the advertisement andweight coefficient of each advertisement original. One advertisement isselected in accordance with the result of that extraction.

In the used rule process 14, a check as to whether distribution ispossible is made with respect to the advertisement original selected bythe distribution list generation process 13, based on the advertisementdata information 15-5. This is because there is a plurality of contentsencoded with respect to an advertisement original, and whether or notthe advertisement original selected by the random extraction processinghas content corresponding to available encoding (a used rule) ischecked. The advertisement data is a plurality of encoded contentinformation linked to the advertisement original, and the used rule isinformation regarding the viewing environment of a viewer. A bit rateand number of pixels are included in the advertisement data and usedrule.

Only advertisements that have passed this check are added to thedistribution list. Advertisement content for which distribution has beenfinalized, and information such as day and time are outputted to thedistribution list generation log 15-7. When an addition is made to thedistribution list, a value that results from subtracting the number ofdistributions from the number of reproductions for the advertisementheld in the pre-checked advertising list is updated as the new number ofreproductions for the advertisement. The updating of the number ofreproductions for the advertisement can also be done periodically, usingthe distribution list generation log 15-7.

In the distribution list generation process 13, the used rule checkingprocess 14 is repeated until the slot size in seconds provided by theadvertisement request is filled. When the slot size in seconds isfilled, the distribution list is returned to the request acceptancesection 11, and distribution is made to the viewer terminal 2.

By analyzing the distribution list generation log 15-7 that is outputtedat the time of distribution, the number of viewings is predicted, andthe next advertising plan is established. In addition, by reflecting thedistribution list generation log that is output each day in the weightcalculation processing, it is possible to perform dynamic distributioncontrol that is responsive to changes in the number of viewings.

As described above, in an information distribution system of the presentinvention, the distribution probability desired by an advertiser can bemaintained without establishing a distribution priority. Thus, comparedwith a conventional method in which distribution is carried out byestablishing a priority sequence, a highly effective distributionschedule capable of advertisement distribution with a narrowed viewertargeting can be created by simple processing.

In addition, because there is no need to establish a priority sequence,even if for example there are complex distribution conditionspecifications from the advertiser, such as category division, time/spotspecifications, emphasis/non-emphasis or disallowance specifications,and the number of content seconds, it is possible to perform uniformprocessing by the same handicapped non-return, random extraction method,and thus there is a great benefit in terms of not only eliminating humansupport, but also avoiding a system architecture of great complexity.

Furthermore, in an advertisement distribution system of the presentinvention, by properly selecting the handicap with regard to eachadvertisement, even if there are various distribution conditionspecifications as noted above, the advertising list, which is the objectof random extraction so as to maintain the extraction probability of theadvertisement of the advertiser, is controlled. Thus, with respect toviewer terminals belonging to the same category, regardless of thedetails of requests such as the time band and video content type from aviewer terminal, it is possible to provide viewing opportunities for thesame advertisement, and it is also possible to achieve advertisementdistribution as desired by the advertiser. Additionally, becausereliable distribution with neither excesses nor shortages with respectto the desired number of reproductions for the advertisement can beprovided by a weight applying method, the advertiser's desires can besatisfied to an even greater degree.

INDUSTRIAL APPLICABILITY

The present invention meets the needs of clients such as advertisers,and also enables the autonomous distribution of information-matched tothe attributes of an accessing terminal. In a sophisticatedinformation-intensive society with developing broadband capabilities,the present invention is thus expected to be used as an informationdistribution control system comprising highly effective informationdistribution.

1. An advertisement distribution system connected via an informationnetwork with at least a video content storage means which stores videocontents, an advertisement storage means which stores advertisementmaterials, and a video content distribution server which selectivelyreads requested video contents from the video content storage means, anddistributes, via an information network, the video content to a viewerterminal that has made a request, and the system comprises, a viewerdatabase, which stores at least information about a minimum unitcategory to which each viewer belongs, and information about the viewinghistory for each viewer, an advertisement distribution conditiondatabase, which stores at least, for each advertisement, informationabout the desired number of reproductions for the advertisement during aplanned time period and information about specifications of increasingor decreasing with respect to each minimum unit category and timeperiod, a means for predicting the number of distribution demands, whichpredicts the number of demanded distributions within the time period foreach minimum unit category, based on the information on the viewinghistory of all viewers, a means for calculating the number of planneddistributions, which calculates the number of planned distributions ofeach advertisement for each minimum unit category, so as to balance thenumber of desired advertisements of each advertisement for each minimumunit category and the number of requested distributions for each minimumunit category, a means for generating a random extraction advertisinglist, which generates an advertising list for each minimum unitcategory, wherein the extraction probability for each advertisement inthe case of random extraction is the ratio of the planned number ofdistributions of each advertisement for each minimum unit category tothe accumulated total for each minimum unit category of the plannednumber of distributions of all the advertisements, a means for handicapapplication, which, when performing random extractions, applies ahandicap, based on the information about specification of increasing ordecreasing, each time to the remaining number of distributions of eachadvertisement comprised by each advertising list, so that the meanextraction probability is maintained over the time period, while causinga deviation in the extraction probability distribution between eachadvertising list at each random extraction, a means for randomextraction, which performs random extraction with respect to theadvertising list corresponding to a minimum unit category to which thedistribution demand terminal belongs, based on the remaining number ofdistributions of each advertisement to which a handicap has beenapplied, so as to select one advertisement, a means for generating adistribution list, which generates a distribution list in which theextraction sequence is used as the advertisement distribution sequence,by repeating the random extraction of advertisements by the means forrandom extraction until the demanded advertisement slots are filled,while updating the advertising list so that the extraction probabilitiesfor the next time reflect the results of the extraction, a means formanaging a distribution list, which stores the distribution list andoutputs the list to an advertisement material distribution server, andan advertisement material distribution server which, based on thedistribution list, sequentially and selectively reads a correspondingadvertisement material from the advertisement material storage means,and distribute the corresponding advertisement via the informationnetwork to a demand terminal which has made a request so as to beinserted into the video content distributed from the video contentdistribution server when the video content is distributed.
 2. Theadvertisement distribution system of claim 1, wherein the means ofgenerating a distribution list generates a distribution list in whichthe extraction sequence is used as the advertisement distributionsequence, by repeating the random extraction of advertisements by themeans for random extraction until the demanded advertisement slots arefilled, while updating each number of planned distributions of theadvertising list by reducing the number of planned distributions so thatthere is no return to the advertising list for the extractedadvertisement.
 3. The advertisement distribution system of claim 1,wherein the means for generating a distribution list generates adistribution list in which the extraction sequence is used as theadvertisement distribution sequence, by repeating the random extractionof advertisements by the means for random extraction until the demandedadvertisement slots are filled, while multiplying the extractionprobability of each advertisement by a corresponding correctioncoefficient and updating the extraction probability of eachadvertisement in the advertising list so that the extraction probabilityfor the next time reflects the extraction results.
 4. The advertisementdistribution system of claim 1, wherein the advertisement distributioncondition database further stores a minimum unit category classificationfor each advertisement, and the system further comprises a means forminimum unit category classification which performs a detailed division,into minimum categories, of the categories for all the advertisementsdesired to be distributed during the time period, and assigning theincrease or decrease specifications stored in the advertisementdistribution condition database to the corresponding minimum categories,and then storing the specifications again.
 5. The advertisementdistribution system of claim 1, wherein the means for calculating thenumber of planned distributions, in order to increase or decrease theinitially allocated number of reproductions for the advertisement forthe specified category for each advertisement in accordance with thetarget specification, performs a uniform flexible adjustment between theinitially allocated number and the number of reproductions for theadvertisement for categories without target specification for theadvertisement; and uses each of the number of reproductions for theadvertisement to which the increase or decrease adjustment has made asthe planned number of distributions for each minimum unit category, sothat the overall number of reproductions for the advertisement comprisedin each minimum unit category agrees with the number of distributiondemands for each minimum unit category, while maintaining the ratio ofthe number of reproductions for each advertisement for each minimum unitcategory to the overall number of planned reproductions foradvertisements comprised in each minimum unit category after theflexible adjustment.
 6. An advertisement distribution method comprisingconnecting through an information network to at least a video contentstorage means which stores video contents, an advertisement, storagemeans which stores advertisement materials, and a video contentdistribution server which selectively reads a requested video contentsfrom the video content storage means, and distributes via an informationnetwork the video content to a viewer terminal that has made a request,and the method further comprises the steps of: storing at leastinformation about a minimum unit category to which each viewer belongs,and information about the viewing history for each viewer, storing atleast, for each advertisement, information about the desired number ofreproductions for the advertisement during a planned time period andinformation about specifications of increasing or decreasing withrespect to each minimum unit category and time period, predicting thenumber of distribution demands within the time period for each minimumunit category, based on the information on the viewing history of allviewers, calculating the number of planned distributions of eachadvertisement for each minimum unit category, so as to balance thenumber of desired advertisements of each advertisement for each minimumunit category and the number of distribution demands for each minimumunit category, generating a random extraction advertising list for eachminimum unit category, in which the extraction probability for eachadvertisement in the case of random extraction is the ratio of theplanned number of distributions of each advertisement for each minimumunit category to the accumulated total for each minimum unit category ofthe planned number of distributions of all the advertisements, applyinghandicap, wherein a handicap is applied, based on the information aboutspecification of increasing or decreasing, each time of randomextractions to the remaining number of distributions of eachadvertisement comprised by each advertising list, so that the meanextraction probability is maintained over the time period, while causinga deviation in the extraction probability distribution between eachadvertising list at each random extraction, extracting one advertisementby selecting and performing random extraction with respect to theadvertising list corresponding to a minimum unit category to which thedistribution demand terminal belongs, based on the remaining number ofdistributions of each advertisement to which a handicap has beenapplied, generating a distribution list in which the extraction sequenceis used as the advertisement distribution sequence, by repeating therandom extraction of advertisements until the demanded advertisementslots are filled, while updating the advertising list so that theextraction probabilities for the next time reflect the results of theextraction, storing the distribution list and outputting the list to anadvertisement material distribution server, sequentially and selectivelyreading a corresponding advertisement material from advertisementstorage mean based on the distribution list, and distributing thecorresponding advertisement material from the advertisement materialdistribution server via the information network to demand terminal whichhas made a request so as to be inserted into the video contentdistributed from the video content distribution when the video contentis distributed.
 7. The advertisement distribution method of claim 6,wherein the step of generating a distribution list generates adistribution list in which the extraction sequence is used as theadvertisement distribution sequence, by repeating the random extractionof advertisements by the step of extracting one advertisement until thedemanded advertisement slots are filled, while updating each number ofplanned distributions of the extracted advertisement by reducing it sothat there is no return to the advertising list for the randomextraction.
 8. The advertisement distribution method of claim 6, whereinthe step of generating a distribution list generates a distribution listin which the extraction sequence is used as the advertisementdistribution sequence, by repeating the random extraction ofadvertisements by the step of extracting one advertisement until thedemanded advertisement slots are filled, while multiplying theextraction probability of each advertisement by a correspondingcorrection coefficient and updating the extraction probability of eachadvertisement in the advertising list so that the extraction probabilityfor the next time reflects the extraction results.
 9. The advertisementdistribution method of claim 6, wherein the method comprises the stepsof: storing a category classification for each advertisement, finelydividing the categories for all the advertisements desired to bedistributed during the time period, into minimum categories, andassigning the stored increase or decrease specifications to thecorresponding minimum unit categories, and then storing thespecifications again.
 10. The advertisement distribution method of claim6, wherein the step of calculating the number of planned distributions,in order to increase or decrease the initially allocated number ofreproductions for the advertisement for the specified category for eachadvertisement in accordance with the target specification, performs auniform flexible adjustment between the initially allocated number andthe number of reproductions for the advertisement for minimum unitcategories without target specification for the advertisement; and useseach of the number of reproductions for the advertisement to which theincrease or decrease adjustment has made as the planned number ofdistributions for each minimum unit category, so that the overall numberof reproductions for the advertisement comprised in each minimum unitcategory agrees with the number of distribution demands for each minimumunit category, while maintaining the ratio of the number ofreproductions for each advertisement for each minimum unit category tothe overall number of planned reproductions for advertisements comprisedin each minimum unit category after the flexible adjustment.
 11. Anadvertisement distribution system that distributes each advertisementmaterial from an advertisement distribution server to an informationdemand terminal via an information network, where the system comprises:a means for managing the number of distributions, where the means storesthe planned number of distributions during a period of time for eachadvertisement material, the actual number of distributions already madefor each advertisement material, and the remaining number ofdistributions for each advertisement material, which is the differencebetween these two numbers of distributions, a means for generatingadvertising list, where the means generates an advertising list forextraction of each time period, in which the extraction probability foreach advertisement material in the case of random extraction is theratio of the remaining number of distributions for each advertisementmaterial to the accumulated total of the remaining number ofdistributions for each advertisement material at that point in time, ameans for handicap application, which, when performing randomextractions, applies a handicap, based on information aboutspecification of increasing or decreasing, each time to the remainingnumber of distributions of each advertisement material comprised by theadvertising list, so that the mean extraction probability is maintainedover the time period, while causing deviation in the extractionprobability distribution between each advertising list at each randomextraction, a means for random extraction, where the means performsrandom extractions with respect to the advertising list of thecorresponding time period, based on the remaining number ofdistributions of each advertisement material to which a handicap hasbeen applied, so as to extract one advertisement material, and anadvertisement material distribution server which distributes anextracted advertisement material via the information network to thedistribution demand terminal, wherein an addition is made to the actualnumber of distributions already made, a subtraction is made from theremaining number of distributions based on the results of thedistribution, and wherein the advertising list is updated so that thedistribution results are reflected in the extraction probabilities fornext time.
 12. An advertisement distribution method that distributeseach advertisement material from an advertisement distribution server toan information demand terminal via an information network, where themethod comprises the steps of: managing the number of distributions,wherein the planned number of distributions during a period of time foreach advertisement material, the actual number of distributions alreadymade for each advertisement material, and the remaining number ofdistributions for each advertisement material, which is the differencebetween these two numbers of distributions, are stored, generating anadvertising list for extraction of each time period, in which theextraction probability for each advertisement material in the case ofrandom extraction is the ratio of the remaining number of distributionsfor each advertisement material to the accumulated total of theremaining number of distributions for each advertisement material atthat point in time, applying handicap, wherein, when performing randomextractions, a handicap is applied, based on information aboutspecification of increasing or decreasing, each time to the remainingnumber of distributions of each advertisement material comprised by theadvertising list, so that the mean extraction probability is maintainedover the time period, while causing deviation in the extractionprobability distribution between each advertising list at each randomextraction, extracting one advertisement material by performing a randomextraction with respect to the advertising list of the correspondingtime period, based on the remaining number of distributions of eachadvertisement material to which a handicap has been applied,distributing the extracted advertisement material from an advertisementdistribution server via the information network to the distributiondemand terminal, and updating the advertising list so that thedistribution results are reflected in the extraction probabilities fornext time.